Regression (Phase-based) SUPER CLEAN

Init

Set Working Directory

Imports

Input and Output Directories and Files

Check Period and Phase in df2

Check Period and Phase in df3

Prepare for Regression

./data/20240428T200156-politicians-aux-analysis/n0001-init//n0001-models-phase-i0008-all/fit0x0.extension 

Fitting and Marginalization

Cleanup

Save Data for Reference

Source Helpers

Model fit01aPh: Null

Fit

fit01aPh: [df0] Agency ~ (1 | Name) + 1
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: Agency ~ (1 | Name) + 1
   Data: df0
Control: control

REML criterion at convergence: 26631.7

Scaled residuals: 
    Min      1Q  Median      3Q     Max 
-7.9514 -0.5639 -0.0023  0.5683  7.3986 

Random effects:
 Groups   Name        Variance Std.Dev.
 Name     (Intercept) 0.006209 0.0788  
 Residual             0.067519 0.2598  
Number of obs: 169997, groups:  Name, 870

Fixed effects:
             Estimate Std. Error        df t value Pr(>|t|)    
(Intercept) 4.986e-01  2.807e-03 8.264e+02   177.7   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--------------------------------------------------------------------- 
fit01aPh: [df0] Agency ~ (1 | Name) + 1
# R2 for Mixed Models

  Conditional R2: 0.084
     Marginal R2: 0.000
--------------------------------------------------------------------- 
fit01aPh: [df0] Agency ~ (1 | Name) + 1
# Intraclass Correlation Coefficient

    Adjusted ICC: 0.084
  Unadjusted ICC: 0.084
--------------------------------------------------------------------- 
fit01aPh: [df0] Agency ~ (1 | Name) + 1
# ICC by Group

Group |   ICC
-------------
Name  | 0.084
--------------------------------------------------------------------- 

Efects: Random

Model fit02aPh: Time

Fit

fit02aPh: [df0] Agency ~ (Time | Name) + Time
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: Agency ~ (Time | Name) + Time
   Data: df0
Control: control

REML criterion at convergence: 24941.9

Scaled residuals: 
    Min      1Q  Median      3Q     Max 
-8.0353 -0.5639 -0.0047  0.5664  7.3362 

Random effects:
 Groups   Name        Variance Std.Dev. Corr
 Name     (Intercept) 0.006283 0.07927      
          Time        0.004088 0.06394  0.18
 Residual             0.066384 0.25765      
Number of obs: 169997, groups:  Name, 870

Fixed effects:
              Estimate Std. Error         df t value Pr(>|t|)    
(Intercept)   0.498029   0.002848 816.443563 174.884  < 2e-16 ***
Time         -0.010230   0.002634 709.116999  -3.884 0.000112 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--------------------------------------------------------------------- 
fit02aPh: [df0] Agency ~ (Time | Name) + Time
# R2 for Mixed Models

  Conditional R2: 0.102
     Marginal R2: 0.000
--------------------------------------------------------------------- 
fit02aPh: [df0] Agency ~ (Time | Name) + Time
# Intraclass Correlation Coefficient

    Adjusted ICC: 0.102
  Unadjusted ICC: 0.102
--------------------------------------------------------------------- 
fit02aPh: [df0] Agency ~ (Time | Name) + Time
# ICC by Group

Group |   ICC
-------------
Name  | 0.085
--------------------------------------------------------------------- 

Effects: Time

Compute

fit02aPh: [df0] Agency ~ (Time | Name) + Time

===================================================================== 

# Average predicted values of Agency

 Time | Predicted |     95% CI
------------------------------
-1.00 |      0.51 | 0.50, 0.51
-0.50 |      0.50 | 0.50, 0.51
 0.00 |      0.50 | 0.49, 0.50
 0.50 |      0.50 | 0.49, 0.50
 1.00 |      0.49 | 0.48, 0.50

===================================================================== 

# (Average) Linear trend for Time

Slope     |       95% CI |     p
--------------------------------
-7.57e-03 | -0.01,  0.00 | 0.004

===================================================================== 

# (Average) Linear trend for Time

Slope     |       95% CI |     p
--------------------------------
-7.57e-03 | -0.01,  0.00 | 0.004

Plot: Basic

Model fit03aPh: Time x Phase

Fit

fit03aPh: [df0] Agency ~ (Time | Name) + Time * Phase
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: Agency ~ (Time | Name) + Time * Phase
   Data: df0
Control: control

REML criterion at convergence: 24043.7

Scaled residuals: 
    Min      1Q  Median      3Q     Max 
-8.1156 -0.5629 -0.0072  0.5649  7.3761 

Random effects:
 Groups   Name        Variance Std.Dev. Corr
 Name     (Intercept) 0.006224 0.07889      
          Time        0.004129 0.06425  0.18
 Residual             0.066017 0.25694      
Number of obs: 169997, groups:  Name, 870

Fixed effects:
               Estimate Std. Error         df t value Pr(>|t|)    
(Intercept)   5.285e-01  3.170e-03  1.284e+03 166.749   <2e-16 ***
Time          4.459e-02  3.657e-03  2.769e+03  12.192   <2e-16 ***
PhaseAE      -4.145e-03  4.178e-03  1.691e+05  -0.992   0.3212    
PhaseBR      -5.689e-01  3.066e-02  1.686e+05 -18.558   <2e-16 ***
PhaseAR      -9.121e-03  4.936e-03  1.697e+05  -1.848   0.0646 .  
Time:PhaseAE -3.579e-01  2.590e-02  1.688e+05 -13.820   <2e-16 ***
Time:PhaseBR  1.610e+00  9.670e-02  1.686e+05  16.650   <2e-16 ***
Time:PhaseAR -9.963e-02  7.213e-03  1.676e+05 -13.812   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--------------------------------------------------------------------- 
fit03aPh: [df0] Agency ~ (Time | Name) + Time * Phase
# R2 for Mixed Models

  Conditional R2: 0.107
     Marginal R2: 0.006
--------------------------------------------------------------------- 
fit03aPh: [df0] Agency ~ (Time | Name) + Time * Phase
# Intraclass Correlation Coefficient

    Adjusted ICC: 0.102
  Unadjusted ICC: 0.101
--------------------------------------------------------------------- 
fit03aPh: [df0] Agency ~ (Time | Name) + Time * Phase
# ICC by Group

Group |   ICC
-------------
Name  | 0.085
--------------------------------------------------------------------- 

Effects: Time

Compute

fit03aPh: [df0] Agency ~ (Time | Name) + Time * Phase

===================================================================== 

# Average predicted values of Agency

 Time | Predicted |     95% CI
------------------------------
-1.00 |      0.45 | 0.44, 0.47
-0.50 |      0.48 | 0.47, 0.49
 0.00 |      0.50 | 0.50, 0.51
 0.50 |      0.53 | 0.52, 0.54
 1.00 |      0.56 | 0.54, 0.57

===================================================================== 

# (Average) Linear trend for Time

Slope |     95% CI |      p
---------------------------
0.05  | 0.04, 0.06 | < .001

===================================================================== 

# (Average) Linear trend for Time

Slope |     95% CI |      p
---------------------------
0.05  | 0.04, 0.06 | < .001

Plot: Basic

Effects: Phase

Compute

fit03aPh: [df0] Agency ~ (Time | Name) + Time * Phase

===================================================================== 

# Average predicted values of Agency

Phase | Predicted |       95% CI
--------------------------------
BE    |      0.53 |  0.52,  0.53
AE    |      0.55 |  0.54,  0.56
BR    |     -0.15 | -0.22, -0.08
AR    |      0.53 |  0.51,  0.54

===================================================================== 

Phase | Predicted |       95% CI |      p
-----------------------------------------
BE    |      0.53 |  0.52,  0.53 | < .001
AE    |      0.55 |  0.54,  0.56 | < .001
BR    |     -0.15 | -0.22, -0.08 | < .001
AR    |      0.53 |  0.51,  0.54 | < .001

===================================================================== 

# Pairwise comparisons

Phase | Contrast |       95% CI |      p
----------------------------------------
BE-AE |    -0.02 | -0.03, -0.01 | < .001
BE-BR |     0.68 |  0.61,  0.75 | < .001
BE-AR | 2.34e-03 | -0.01,  0.01 | 0.658 
AE-BR |     0.70 |  0.63,  0.77 | < .001
AE-AR |     0.02 |  0.01,  0.04 | 0.003 
BR-AR |    -0.68 | -0.75, -0.60 | < .001

Plot: Basic

Effects: Time x Phase

Compute

fit03aPh: [df0] Agency ~ (Time | Name) + Time * Phase

===================================================================== 

# Average predicted values of Agency

Phase: BE

 Time | Predicted |      95% CI
-------------------------------
-1.00 |      0.48 | 0.47,  0.49
-0.50 |      0.51 | 0.50,  0.51
 0.00 |      0.53 | 0.52,  0.54
 0.50 |      0.56 | 0.55,  0.56
 1.00 |      0.58 | 0.57,  0.59

Phase: AE

 Time | Predicted |      95% CI
-------------------------------
-1.00 |      0.84 | 0.78,  0.89
-0.50 |      0.68 | 0.65,  0.71
 0.00 |      0.53 | 0.52,  0.54
 0.50 |      0.37 | 0.35,  0.39
 1.00 |      0.22 | 0.17,  0.26

Phase: BR

 Time | Predicted |       95% CI
--------------------------------
-1.00 |     -1.70 | -1.95, -1.45
-0.50 |     -0.87 | -1.02, -0.71
 0.00 |     -0.04 | -0.10,  0.02
 0.50 |      0.79 |  0.76,  0.83
 1.00 |      1.62 |  1.49,  1.75

Phase: AR

 Time | Predicted |      95% CI
-------------------------------
-1.00 |      0.57 | 0.55,  0.60
-0.50 |      0.55 | 0.53,  0.56
 0.00 |      0.52 | 0.51,  0.53
 0.50 |      0.50 | 0.49,  0.50
 1.00 |      0.47 | 0.46,  0.48

===================================================================== 

# (Average) Linear trend for Time

Phase | Slope |       95% CI |      p
-------------------------------------
BE    |  0.04 |  0.04,  0.05 | < .001
AE    | -0.31 | -0.36, -0.26 | < .001
BR    |  1.65 |  1.47,  1.84 | < .001
AR    | -0.06 | -0.07, -0.04 | < .001

===================================================================== 

# (Average) Linear trend for Time

Phase | Contrast |       95% CI |      p
----------------------------------------
BE-AE |     0.36 |  0.31,  0.41 | < .001
BE-BR |    -1.61 | -1.80, -1.42 | < .001
BE-AR |     0.10 |  0.09,  0.11 | < .001
AE-BR |    -1.97 | -2.16, -1.77 | < .001
AE-AR |    -0.26 | -0.31, -0.21 | < .001
BR-AR |     1.71 |  1.52,  1.90 | < .001

Plot: Basic

Plot: Nicer

Model fit04aPh: Time x Phase x Outcome

Fit

fit04aPh: [df0] Agency ~ (Time | Name) + Time * Phase * Outcome
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: Agency ~ (Time | Name) + Time * Phase * Outcome
   Data: df0
Control: control

REML criterion at convergence: 23540

Scaled residuals: 
    Min      1Q  Median      3Q     Max 
-8.1902 -0.5632 -0.0074  0.5639  7.3864 

Random effects:
 Groups   Name        Variance Std.Dev. Corr 
 Name     (Intercept) 0.004798 0.06927       
          Time        0.003348 0.05786  -0.07
 Residual             0.065916 0.25674       
Number of obs: 169997, groups:  Name, 870

Fixed effects:
                             Estimate Std. Error         df t value Pr(>|t|)
(Intercept)                 5.151e-01  4.450e-03  1.471e+03 115.767  < 2e-16
Time                        5.703e-02  5.597e-03  3.426e+03  10.189  < 2e-16
PhaseAE                    -4.245e-02  7.688e-03  1.693e+05  -5.521 3.38e-08
PhaseBR                    -4.966e-01  6.025e-02  1.690e+05  -8.242  < 2e-16
PhaseAR                    -1.195e-01  1.034e-02  1.662e+05 -11.561  < 2e-16
Outcomewinner               2.383e-02  5.853e-03  1.425e+03   4.072 4.92e-05
Time:PhaseAE               -4.906e-01  5.053e-02  1.692e+05  -9.710  < 2e-16
Time:PhaseBR                1.152e+00  1.903e-01  1.689e+05   6.052 1.44e-09
Time:PhaseAR               -5.823e-02  1.523e-02  1.543e+05  -3.824 0.000131
Time:Outcomewinner         -2.039e-02  7.198e-03  3.276e+03  -2.833 0.004646
PhaseAE:Outcomewinner       5.796e-02  9.165e-03  1.692e+05   6.324 2.56e-10
PhaseBR:Outcomewinner      -9.406e-02  6.997e-02  1.689e+05  -1.344 0.178864
PhaseAR:Outcomewinner       1.478e-01  1.178e-02  1.679e+05  12.550  < 2e-16
Time:PhaseAE:Outcomewinner  1.675e-01  5.885e-02  1.692e+05   2.846 0.004424
Time:PhaseBR:Outcomewinner  6.256e-01  2.209e-01  1.688e+05   2.832 0.004623
Time:PhaseAR:Outcomewinner -4.478e-02  1.731e-02  1.602e+05  -2.586 0.009706
                              
(Intercept)                ***
Time                       ***
PhaseAE                    ***
PhaseBR                    ***
PhaseAR                    ***
Outcomewinner              ***
Time:PhaseAE               ***
Time:PhaseBR               ***
Time:PhaseAR               ***
Time:Outcomewinner         ** 
PhaseAE:Outcomewinner      ***
PhaseBR:Outcomewinner         
PhaseAR:Outcomewinner      ***
Time:PhaseAE:Outcomewinner ** 
Time:PhaseBR:Outcomewinner ** 
Time:PhaseAR:Outcomewinner ** 
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--------------------------------------------------------------------- 
fit04aPh: [df0] Agency ~ (Time | Name) + Time * Phase * Outcome
# R2 for Mixed Models

  Conditional R2: 0.102
     Marginal R2: 0.021
--------------------------------------------------------------------- 
fit04aPh: [df0] Agency ~ (Time | Name) + Time * Phase * Outcome
# Intraclass Correlation Coefficient

    Adjusted ICC: 0.083
  Unadjusted ICC: 0.081
--------------------------------------------------------------------- 
fit04aPh: [df0] Agency ~ (Time | Name) + Time * Phase * Outcome
# ICC by Group

Group |   ICC
-------------
Name  | 0.067
--------------------------------------------------------------------- 

Parameters

fit04aPh: [df0] Agency ~ (Time | Name) + Time * Phase * Outcome

# Fixed Effects

Parameter                              | Coefficient |       SE |         95% CI | t(169977) |      p
-----------------------------------------------------------------------------------------------------
(Intercept)                            |        0.52 | 4.45e-03 | [ 0.51,  0.52] |    115.77 | < .001
Time                                   |        0.06 | 5.60e-03 | [ 0.05,  0.07] |     10.19 | < .001
Phase [AE]                             |       -0.04 | 7.69e-03 | [-0.06, -0.03] |     -5.52 | < .001
Phase [BR]                             |       -0.50 |     0.06 | [-0.61, -0.38] |     -8.24 | < .001
Phase [AR]                             |       -0.12 |     0.01 | [-0.14, -0.10] |    -11.56 | < .001
Outcome [winner]                       |        0.02 | 5.85e-03 | [ 0.01,  0.04] |      4.07 | < .001
Time × Phase [AE]                      |       -0.49 |     0.05 | [-0.59, -0.39] |     -9.71 | < .001
Time × Phase [BR]                      |        1.15 |     0.19 | [ 0.78,  1.52] |      6.05 | < .001
Time × Phase [AR]                      |       -0.06 |     0.02 | [-0.09, -0.03] |     -3.82 | < .001
Time × Outcome [winner]                |       -0.02 | 7.20e-03 | [-0.03, -0.01] |     -2.83 | 0.005 
Phase [AE] × Outcome [winner]          |        0.06 | 9.17e-03 | [ 0.04,  0.08] |      6.32 | < .001
Phase [BR] × Outcome [winner]          |       -0.09 |     0.07 | [-0.23,  0.04] |     -1.34 | 0.179 
Phase [AR] × Outcome [winner]          |        0.15 |     0.01 | [ 0.12,  0.17] |     12.55 | < .001
(Time × Phase [AE]) × Outcome [winner] |        0.17 |     0.06 | [ 0.05,  0.28] |      2.85 | 0.004 
(Time × Phase [BR]) × Outcome [winner] |        0.63 |     0.22 | [ 0.19,  1.06] |      2.83 | 0.005 
(Time × Phase [AR]) × Outcome [winner] |       -0.04 |     0.02 | [-0.08, -0.01] |     -2.59 | 0.010 

# Random Effects

Parameter                  | Coefficient
----------------------------------------
SD (Intercept: Name)       |        0.07
SD (Time: Name)            |        0.06
Cor (Intercept~Time: Name) |       -0.07
SD (Residual)              |        0.26

Summary

fit04aPh: [df0] Agency ~ (Time | Name) + Time * Phase * Outcome

Characteristic	Beta	95% CI1	p-value
Time	0.06	0.05, 0.07	<0.001
Phase
AE - BE	0.01	0.00, 0.03	0.10
BR - BE	-0.64	-0.75, -0.53	<0.001
BR - AE	-0.66	-0.77, -0.55	<0.001
AR - BE	-0.04	-0.06, -0.02	<0.001
AR - AE	-0.05	-0.08, -0.03	<0.001
AR - BR	0.60	0.49, 0.71	<0.001
Outcome
winner - loser	0.04	0.00, 0.08	0.069
Time * Phase
Time * AE	-0.49	-0.59, -0.39	<0.001
Time * BR	1.2	0.78, 1.5	<0.001
Time * AR	-0.06	-0.09, -0.03	<0.001
Time * Outcome
Time * winner	-0.02	-0.03, -0.01	0.005
Phase * Outcome
AE * winner	0.06	0.04, 0.08	<0.001
BR * winner	-0.09	-0.23, 0.04	0.2
AR * winner	0.15	0.12, 0.17	<0.001
Time * Phase * Outcome
Time * AE * winner	0.17	0.05, 0.28	0.004
Time * BR * winner	0.63	0.19, 1.1	0.005
Time * AR * winner	-0.04	-0.08, -0.01	0.010
Name.sd__(Intercept)	0.07
Name.cor__(Intercept).Time	-0.07
Name.sd__Time	0.06
Residual.sd__Observation	0.26
1 CI = Confidence Interval

Effects: Time

Compute

fit04aPh: [df0] Agency ~ (Time | Name) + Time * Phase * Outcome

===================================================================== 

# Average predicted values of Agency

 Time | Predicted |     95% CI
------------------------------
-1.00 |      0.46 | 0.44, 0.47
-0.50 |      0.48 | 0.47, 0.49
 0.00 |      0.50 | 0.50, 0.51
 0.50 |      0.53 | 0.52, 0.54
 1.00 |      0.55 | 0.54, 0.56

===================================================================== 

# (Average) Linear trend for Time

Slope |     95% CI |      p
---------------------------
0.05  | 0.04, 0.06 | < .001

===================================================================== 

# (Average) Linear trend for Time

Slope |     95% CI |      p
---------------------------
0.05  | 0.04, 0.06 | < .001

Plot: Basic

Effects: Phase

Compute

fit04aPh: [df0] Agency ~ (Time | Name) + Time * Phase * Outcome

===================================================================== 

# Average predicted values of Agency

Phase | Predicted |       95% CI
--------------------------------
BE    |      0.52 |  0.52,  0.53
AE    |      0.55 |  0.54,  0.57
BR    |     -0.12 | -0.19, -0.04
AR    |      0.51 |  0.50,  0.52

===================================================================== 

Phase | Predicted |       95% CI |      p
-----------------------------------------
BE    |      0.52 |  0.52,  0.53 | < .001
AE    |      0.55 |  0.54,  0.57 | < .001
BR    |     -0.12 | -0.19, -0.04 | 0.004 
AR    |      0.51 |  0.50,  0.52 | < .001

===================================================================== 

# Pairwise comparisons

Phase | Contrast |       95% CI |      p
----------------------------------------
BE-AE |    -0.03 | -0.04, -0.02 | < .001
BE-BR |     0.64 |  0.56,  0.72 | < .001
BE-AR |     0.02 |  0.00,  0.03 | 0.007 
AE-BR |     0.67 |  0.59,  0.75 | < .001
AE-AR |     0.05 |  0.03,  0.06 | < .001
BR-AR |    -0.62 | -0.70, -0.55 | < .001

Plot: Basic

Effects: Time x Phase

Compute

fit04aPh: [df0] Agency ~ (Time | Name) + Time * Phase * Outcome

===================================================================== 

# Average predicted values of Agency

Phase: BE

 Time | Predicted |      95% CI
-------------------------------
-1.00 |      0.48 | 0.48,  0.49
-0.50 |      0.51 | 0.50,  0.51
 0.00 |      0.53 | 0.52,  0.53
 0.50 |      0.55 | 0.54,  0.56
 1.00 |      0.57 | 0.56,  0.58

Phase: AE

 Time | Predicted |      95% CI
-------------------------------
-1.00 |      0.86 | 0.80,  0.92
-0.50 |      0.69 | 0.66,  0.72
 0.00 |      0.53 | 0.52,  0.53
 0.50 |      0.36 | 0.34,  0.38
 1.00 |      0.19 | 0.15,  0.24

Phase: BR

 Time | Predicted |       95% CI
--------------------------------
-1.00 |     -1.65 | -1.90, -1.40
-0.50 |     -0.84 | -1.00, -0.69
 0.00 |     -0.03 | -0.09,  0.03
 0.50 |      0.78 |  0.74,  0.81
 1.00 |      1.59 |  1.46,  1.72

Phase: AR

 Time | Predicted |      95% CI
-------------------------------
-1.00 |      0.55 | 0.53,  0.58
-0.50 |      0.53 | 0.51,  0.55
 0.00 |      0.51 | 0.50,  0.52
 0.50 |      0.49 | 0.48,  0.49
 1.00 |      0.47 | 0.46,  0.47

===================================================================== 

# (Average) Linear trend for Time

Phase |     Slope |       95% CI |      p
-----------------------------------------
BE    |      0.06 |  0.05,  0.07 | < .001
AE    |     -0.43 | -0.53, -0.33 | < .001
BR    |      1.21 |  0.84,  1.58 | < .001
AR    | -1.19e-03 | -0.03,  0.03 | 0.936 

===================================================================== 

# (Average) Linear trend for Time

Phase | Contrast |       95% CI |      p
----------------------------------------
BE-AE |     0.49 |  0.39,  0.59 | < .001
BE-BR |    -1.15 | -1.52, -0.78 | < .001
BE-AR |     0.06 |  0.03,  0.09 | < .001
AE-BR |    -1.64 | -2.03, -1.26 | < .001
AE-AR |    -0.43 | -0.53, -0.33 | < .001
BR-AR |     1.21 |  0.84,  1.58 | < .001

Plot: Basic

Effects: Phase x Outcome

Compute

fit04aPh: [df0] Agency ~ (Time | Name) + Time * Phase * Outcome

===================================================================== 

# Average predicted values of Agency

Outcome: loser

Phase | Predicted |       95% CI
--------------------------------
BE    |      0.51 |  0.50,  0.52
AE    |      0.50 |  0.48,  0.52
BR    |     -0.07 | -0.21,  0.08
AR    |      0.39 |  0.37,  0.42

Outcome: winner

Phase | Predicted |       95% CI
--------------------------------
BE    |      0.53 |  0.53,  0.54
AE    |      0.57 |  0.56,  0.59
BR    |     -0.18 | -0.26, -0.09
AR    |      0.57 |  0.56,  0.58

===================================================================== 

Phase | Outcome | Predicted |       95% CI |      p
---------------------------------------------------
BE    |   loser |      0.51 |  0.50,  0.52 | < .001
AE    |   loser |      0.50 |  0.48,  0.52 | < .001
BR    |   loser |     -0.07 | -0.21,  0.08 | 0.364 
AR    |   loser |      0.39 |  0.37,  0.42 | < .001
BE    |  winner |      0.53 |  0.53,  0.54 | < .001
AE    |  winner |      0.57 |  0.56,  0.59 | < .001
BR    |  winner |     -0.18 | -0.26, -0.09 | < .001
AR    |  winner |      0.57 |  0.56,  0.58 | < .001

===================================================================== 

# Pairwise comparisons

Phase |       Outcome | Contrast |       95% CI |      p
--------------------------------------------------------
BE-AE |   loser-loser | 9.06e-03 | -0.01,  0.03 | 0.404 
BE-BR |   loser-loser |     0.57 |  0.43,  0.72 | < .001
BE-AR |   loser-loser |     0.12 |  0.09,  0.14 | < .001
BE-BE |  loser-winner |    -0.03 | -0.04, -0.01 | < .001
BE-AE |  loser-winner |    -0.06 | -0.08, -0.05 | < .001
BE-BR |  loser-winner |     0.69 |  0.60,  0.77 | < .001
BE-AR |  loser-winner |    -0.06 | -0.08, -0.05 | < .001
AE-BR |   loser-loser |     0.57 |  0.42,  0.71 | < .001
AE-AR |   loser-loser |     0.11 |  0.08,  0.14 | < .001
AE-BE |  loser-winner |    -0.03 | -0.06, -0.01 | 0.003 
AE-AE |  loser-winner |    -0.07 | -0.10, -0.05 | < .001
AE-BR |  loser-winner |     0.68 |  0.59,  0.76 | < .001
AE-AR |  loser-winner |    -0.07 | -0.09, -0.04 | < .001
BR-AR |   loser-loser |    -0.46 | -0.60, -0.31 | < .001
BR-BE |  loser-winner |    -0.60 | -0.74, -0.46 | < .001
BR-AE |  loser-winner |    -0.64 | -0.78, -0.49 | < .001
BR-BR |  loser-winner |     0.11 | -0.06,  0.28 | 0.205 
BR-AR |  loser-winner |    -0.64 | -0.78, -0.49 | < .001
AR-BE |  loser-winner |    -0.14 | -0.16, -0.12 | < .001
AR-AE |  loser-winner |    -0.18 | -0.20, -0.15 | < .001
AR-BR |  loser-winner |     0.57 |  0.48,  0.66 | < .001
AR-AR |  loser-winner |    -0.18 | -0.20, -0.15 | < .001
BE-AE | winner-winner |    -0.04 | -0.05, -0.02 | < .001
BE-BR | winner-winner |     0.71 |  0.63,  0.80 | < .001
BE-AR | winner-winner |    -0.04 | -0.05, -0.02 | < .001
AE-BR | winner-winner |     0.75 |  0.66,  0.83 | < .001
AE-AR | winner-winner | 2.17e-03 | -0.01,  0.02 | 0.800 
BR-AR | winner-winner |    -0.75 | -0.83, -0.66 | < .001

Plot: Basic

Effects: Time x Phase x Outcome

Compute

fit04aPh: [df0] Agency ~ (Time | Name) + Time * Phase * Outcome

===================================================================== 

# Average predicted values of Agency

Outcome: loser
Phase: BE

 Time | Predicted |      95% CI
-------------------------------
-1.00 |      0.45 | 0.44,  0.46
-0.50 |      0.48 | 0.47,  0.49
 0.00 |      0.51 | 0.50,  0.52
 0.50 |      0.54 | 0.53,  0.55
 1.00 |      0.57 | 0.56,  0.59

Outcome: loser
Phase: AE

 Time | Predicted |       95% CI
--------------------------------
-1.00 |      0.90 |  0.79,  1.01
-0.50 |      0.69 |  0.62,  0.75
 0.00 |      0.47 |  0.45,  0.49
 0.50 |      0.25 |  0.22,  0.29
 1.00 |      0.04 | -0.05,  0.13

Outcome: loser
Phase: BR

 Time | Predicted |       95% CI
--------------------------------
-1.00 |     -1.20 | -1.69, -0.70
-0.50 |     -0.59 | -0.89, -0.29
 0.00 |      0.02 | -0.10,  0.13
 0.50 |      0.62 |  0.55,  0.69
 1.00 |      1.23 |  0.97,  1.48

Outcome: loser
Phase: AR

 Time | Predicted |      95% CI
-------------------------------
-1.00 |      0.39 | 0.34,  0.44
-0.50 |      0.39 | 0.36,  0.43
 0.00 |      0.39 | 0.37,  0.41
 0.50 |      0.39 | 0.38,  0.40
 1.00 |      0.39 | 0.38,  0.41

Outcome: winner
Phase: BE

 Time | Predicted |      95% CI
-------------------------------
-1.00 |      0.50 | 0.49,  0.51
-0.50 |      0.52 | 0.51,  0.52
 0.00 |      0.54 | 0.53,  0.54
 0.50 |      0.56 | 0.55,  0.57
 1.00 |      0.58 | 0.56,  0.59

Outcome: winner
Phase: AE

 Time | Predicted |      95% CI
-------------------------------
-1.00 |      0.84 | 0.77,  0.90
-0.50 |      0.69 | 0.66,  0.73
 0.00 |      0.55 | 0.54,  0.56
 0.50 |      0.41 | 0.39,  0.43
 1.00 |      0.27 | 0.22,  0.32

Outcome: winner
Phase: BR

 Time | Predicted |       95% CI
--------------------------------
-1.00 |     -1.87 | -2.16, -1.58
-0.50 |     -0.96 | -1.14, -0.78
 0.00 |     -0.05 | -0.12,  0.02
 0.50 |      0.85 |  0.81,  0.90
 1.00 |      1.76 |  1.61,  1.91

Outcome: winner
Phase: AR

 Time | Predicted |      95% CI
-------------------------------
-1.00 |      0.63 | 0.60,  0.65
-0.50 |      0.60 | 0.58,  0.62
 0.00 |      0.56 | 0.55,  0.58
 0.50 |      0.53 | 0.53,  0.54
 1.00 |      0.50 | 0.49,  0.51

===================================================================== 

# (Average) Linear trend for Time

Outcome | Phase |     Slope |       95% CI |      p
---------------------------------------------------
loser   |    BE |      0.06 |  0.05,  0.07 | < .001
loser   |    AE |     -0.43 | -0.53, -0.33 | < .001
loser   |    BR |      1.21 |  0.84,  1.58 | < .001
loser   |    AR | -1.19e-03 | -0.03,  0.03 | 0.936 
winner  |    BE |      0.04 |  0.03,  0.05 | < .001
winner  |    AE |     -0.29 | -0.35, -0.23 | < .001
winner  |    BR |      1.81 |  1.59,  2.03 | < .001
winner  |    AR |     -0.07 | -0.08, -0.05 | < .001

===================================================================== 

# (Average) Linear trend for Time

Outcome       | Phase | Contrast |       95% CI |      p
--------------------------------------------------------
loser-loser   | BE-AE |     0.49 |  0.39,  0.59 | < .001
loser-loser   | BE-BR |    -1.15 | -1.52, -0.78 | < .001
loser-loser   | BE-AR |     0.06 |  0.03,  0.09 | < .001
loser-winner  | BE-BE |     0.02 |  0.01,  0.03 | 0.005 
loser-winner  | BE-AE |     0.34 |  0.28,  0.40 | < .001
loser-winner  | BE-BR |    -1.76 | -1.98, -1.54 | < .001
loser-winner  | BE-AR |     0.12 |  0.10,  0.14 | < .001
loser-loser   | AE-BR |    -1.64 | -2.03, -1.26 | < .001
loser-loser   | AE-AR |    -0.43 | -0.53, -0.33 | < .001
loser-winner  | AE-BE |    -0.47 | -0.57, -0.37 | < .001
loser-winner  | AE-AE |    -0.15 | -0.26, -0.03 | 0.013 
loser-winner  | AE-BR |    -2.25 | -2.49, -2.01 | < .001
loser-winner  | AE-AR |    -0.37 | -0.47, -0.27 | < .001
loser-loser   | BR-AR |     1.21 |  0.84,  1.58 | < .001
loser-winner  | BR-BE |     1.17 |  0.80,  1.55 | < .001
loser-winner  | BR-AE |     1.50 |  1.12,  1.87 | < .001
loser-winner  | BR-BR |    -0.61 | -1.04, -0.17 | 0.007 
loser-winner  | BR-AR |     1.28 |  0.90,  1.65 | < .001
loser-winner  | AR-BE |    -0.04 | -0.07, -0.01 | 0.015 
loser-winner  | AR-AE |     0.29 |  0.22,  0.35 | < .001
loser-winner  | AR-BR |    -1.82 | -2.04, -1.59 | < .001
loser-winner  | AR-AR |     0.07 |  0.03,  0.10 | < .001
winner-winner | BE-AE |     0.32 |  0.26,  0.38 | < .001
winner-winner | BE-BR |    -1.78 | -2.00, -1.56 | < .001
winner-winner | BE-AR |     0.10 |  0.09,  0.12 | < .001
winner-winner | AE-BR |    -2.10 | -2.33, -1.87 | < .001
winner-winner | AE-AR |    -0.22 | -0.28, -0.16 | < .001
winner-winner | BR-AR |     1.88 |  1.66,  2.10 | < .001

Filter test table

# A tibble: 16 × 7
   Time  Outcome      Phase Contrast conf.low conf.high  p.value
   <chr> <chr>        <chr>    <dbl>    <dbl>     <dbl>    <dbl>
 1 slope loser-winner AE     -0.147  -0.262     -0.0321 1.27e- 2
 2 slope loser-winner AR      0.0652  0.0321     0.0982 1.34e- 4
 3 slope loser-winner BE      0.0204  0.00628    0.0345 5.18e- 3
 4 slope loser-winner BR     -0.605  -1.04      -0.172  6.62e- 3
 5 slope loser        AE-AR  -0.432  -0.535     -0.330  2.45e-16
 6 slope loser        AE-BR  -1.64   -2.03      -1.26   1.47e-16
 7 slope loser        BE-AE   0.491   0.392      0.590  7.06e-22
 8 slope loser        BE-AR   0.0582  0.0284     0.0881 1.53e- 4
 9 slope loser        BE-BR  -1.15   -1.52      -0.779  1.82e- 9
10 slope loser        BR-AR   1.21    0.836      1.58   3.23e-10
11 slope winner       AE-AR  -0.220  -0.281     -0.160  1.55e-12
12 slope winner       AE-BR  -2.10   -2.33      -1.87   5.37e-72
13 slope winner       BE-AE   0.323   0.264      0.382  2.74e-26
14 slope winner       BE-AR   0.103   0.0869     0.119  2.74e-35
15 slope winner       BE-BR  -1.78   -2.00      -1.56   9.36e-56
16 slope winner       BR-AR   1.88    1.66       2.10   7.56e-62

Plot: Basic

Plot: Nicer

Save Workspace

Model fit04xPh: Time x Phase x Outcome

Prepare Data for the Re-scaled Model

   [,1] [,2] [,3]
BE    1    0    0
AE    0    1    0
BR    0    0    1
AR   -1   -1   -1

       [,1]
loser     1
winner   -1

Fit

fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome
   Data: df8
Control: control

REML criterion at convergence: 23562.2

Scaled residuals: 
    Min      1Q  Median      3Q     Max 
-8.1902 -0.5632 -0.0074  0.5639  7.3864 

Random effects:
 Groups   Name        Variance Std.Dev. Corr 
 Name     (Intercept) 0.004849 0.06963       
          TimeC       0.003347 0.05786  -0.12
 Residual             0.065916 0.25674       
Number of obs: 169997, groups:  Name, 870

Fixed effects:
                        Estimate Std. Error         df t value Pr(>|t|)    
(Intercept)           -1.430e-01  1.111e-02  1.138e+05 -12.873  < 2e-16 ***
TimeC                  2.911e-01  2.871e-02  1.687e+05  10.141  < 2e-16 ***
Phase1                 1.673e-01  1.088e-02  1.689e+05  15.372  < 2e-16 ***
Phase2                 1.815e-01  1.164e-02  1.688e+05  15.591  < 2e-16 ***
Phase3                -4.760e-01  3.189e-02  1.689e+05 -14.925  < 2e-16 ***
Outcome1              -2.021e-02  1.111e-02  1.138e+05  -1.819  0.06893 .  
TimeC:Phase1          -2.443e-01  2.870e-02  1.689e+05  -8.510  < 2e-16 ***
TimeC:Phase2          -6.511e-01  3.535e-02  1.690e+05 -18.419  < 2e-16 ***
TimeC:Phase3           1.220e+00  8.317e-02  1.689e+05  14.671  < 2e-16 ***
TimeC:Outcome1        -8.335e-02  2.871e-02  1.687e+05  -2.904  0.00369 ** 
Phase1:Outcome1        7.600e-03  1.088e-02  1.689e+05   0.698  0.48496    
Phase2:Outcome1       -1.568e-02  1.164e-02  1.688e+05  -1.347  0.17804    
Phase3:Outcome1        7.591e-02  3.189e-02  1.689e+05   2.380  0.01730 *  
TimeC:Phase1:Outcome1  9.355e-02  2.870e-02  1.689e+05   3.259  0.00112 ** 
TimeC:Phase2:Outcome1  9.791e-03  3.535e-02  1.690e+05   0.277  0.78180    
TimeC:Phase3:Outcome1 -2.193e-01  8.317e-02  1.689e+05  -2.636  0.00838 ** 
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--------------------------------------------------------------------- 
fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome
# R2 for Mixed Models

  Conditional R2: 0.102
     Marginal R2: 0.021
--------------------------------------------------------------------- 
fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome
# Intraclass Correlation Coefficient

    Adjusted ICC: 0.083
  Unadjusted ICC: 0.081
--------------------------------------------------------------------- 
fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome
# ICC by Group

Group |   ICC
-------------
Name  | 0.067
--------------------------------------------------------------------- 

Performance: Check Model (EXPERIMENTAL)

fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome

Save checks plot

fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome

Performance: Check Collinearity

fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome

Performance: Check Convergence

fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome

[1] TRUE
attr(,"gradient")
[1] 4.648806e-06

Performance: Check Heteroscedasticity

fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome

Warning: Heteroscedasticity (non-constant error variance) detected (p < .001).

Performance: Check Homogeneity

fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome

Performance: Check Outliers

fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome

OK: No outliers detected.
- Based on the following method and threshold: cook (0.7).
- For variable: (Whole model)

Performance: Check Overdispersion

fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome

# Overdispersion test

 dispersion ratio = 0.992
          p-value = 0.152

Performance: Check Predictions

fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome

Warning: Minimum value of original data is not included in the
  replicated data.
  Model may not capture the variation of the data.Warning: Maximum value of original data is not included in the
  replicated data.
  Model may not capture the variation of the data.

Performance: Check Singularity

fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome

[1] FALSE

Performance: Check Zeroinflation

fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome

Performance

Reclaim Model fit04aPh

fit04aPh 

Score

Comparison of Model Performance Indices
Name	Model	R2 (cond.)	R2 (marg.)	ICC	RMSE	Sigma	AIC weights	AICc weights	BIC weights	Performance-Score
fit04aPh	lmerModLmerTest	0.10	0.02	0.08	0.26	0.26	1.00	1.00	1.00	84.61%
fit03aPh	lmerModLmerTest	0.11	6.03e-03	0.10	0.26	0.26	2.51e-118	2.51e-118	7.03e-101	52.18%
fit02aPh	lmerModLmerTest	0.10	4.62e-04	0.10	0.26	0.26	9.57e-321	9.58e-321	3.26e-290	40.78%
fit01aPh	lmerModLmerTest	0.08	0.00	0.08	0.26	0.26	0.00e+00	0.00e+00	0.00e+00	0.99%
NA

Performance Table Sorted by R2_conditional

Comparison of Model Performance Indices
Name	Model	R2 (cond.)	R2 (marg.)	ICC	RMSE	Sigma	AIC weights	AICc weights	BIC weights	Performance-Score
fit03aPh	lmerModLmerTest	0.11	6.03e-03	0.10	0.26	0.26	2.51e-118	2.51e-118	7.03e-101	52.18%
fit02aPh	lmerModLmerTest	0.10	4.62e-04	0.10	0.26	0.26	9.57e-321	9.58e-321	3.26e-290	40.78%
fit04aPh	lmerModLmerTest	0.10	0.02	0.08	0.26	0.26	1.00	1.00	1.00	84.61%
fit01aPh	lmerModLmerTest	0.08	0.00	0.08	0.26	0.26	0.00e+00	0.00e+00	0.00e+00	0.99%
NA

Performance Table Sorted by R2_marginal

Comparison of Model Performance Indices
Name	Model	R2 (cond.)	R2 (marg.)	ICC	RMSE	Sigma	AIC weights	AICc weights	BIC weights	Performance-Score
fit04aPh	lmerModLmerTest	0.10	0.02	0.08	0.26	0.26	1.00	1.00	1.00	84.61%
fit03aPh	lmerModLmerTest	0.11	6.03e-03	0.10	0.26	0.26	2.51e-118	2.51e-118	7.03e-101	52.18%
fit02aPh	lmerModLmerTest	0.10	4.62e-04	0.10	0.26	0.26	9.57e-321	9.58e-321	3.26e-290	40.78%
fit01aPh	lmerModLmerTest	0.08	0.00	0.08	0.26	0.26	0.00e+00	0.00e+00	0.00e+00	0.99%
NA

Interpret R2

weak 

weak 

Plot models

Tabulate Models

	Model 1		Model 2		Model 3		Model 4
Predictors	Estimates	CI	Estimates	CI	Estimates	CI	Estimates	CI
(Intercept)	0.50 ***	0.49 – 0.50	0.50 ***	0.49 – 0.50	0.53 ***	0.52 – 0.53	0.52 ***	0.51 – 0.52
Time			-0.01 ***	-0.02 – -0.01	0.04 ***	0.04 – 0.05	0.06 ***	0.05 – 0.07
Phase [AE]					-0.00	-0.01 – 0.00	-0.04 ***	-0.06 – -0.03
Phase [BR]					-0.57 ***	-0.63 – -0.51	-0.50 ***	-0.61 – -0.38
Phase [AR]					-0.01	-0.02 – 0.00	-0.12 ***	-0.14 – -0.10
Time × Phase [AE]					-0.36 ***	-0.41 – -0.31	-0.49 ***	-0.59 – -0.39
Time × Phase [BR]					1.61 ***	1.42 – 1.80	1.15 ***	0.78 – 1.52
Time × Phase [AR]					-0.10 ***	-0.11 – -0.09	-0.06 ***	-0.09 – -0.03
Outcome [winner]							0.02 ***	0.01 – 0.04
Time × Outcome [winner]							-0.02 **	-0.03 – -0.01
Phase [AE] × Outcome [winner]							0.06 ***	0.04 – 0.08
Phase [BR] × Outcome [winner]							-0.09	-0.23 – 0.04
Phase [AR] × Outcome [winner]							0.15 ***	0.12 – 0.17
(Time × Phase [AE]) × Outcome [winner]							0.17 **	0.05 – 0.28
(Time × Phase [BR]) × Outcome [winner]							0.63 **	0.19 – 1.06
(Time × Phase [AR]) × Outcome [winner]							-0.04 **	-0.08 – -0.01
Random Effects
σ2	0.07		0.07		0.07		0.07
τ00	0.01 Name		0.01 Name		0.01 Name		0.00 Name
τ11			0.00 Name.Time		0.00 Name.Time		0.00 Name.Time
ρ01			0.18 Name		0.18 Name		-0.07 Name
ICC	0.08		0.10		0.10		0.08
N	870 Name		870 Name		870 Name		870 Name
Observations	169997		169997		169997		169997
Marginal R2 / Conditional R2	0.000 / 0.084		0.000 / 0.102		0.006 / 0.107		0.021 / 0.102
* p<0.05   ** p<0.01   *** p<0.001

./data/20240428T200156-politicians-aux-analysis/n0001-init//n0001-models-phase-i0008-all/summary-tab-model-i0001-base.html 

• tab_model

Report fit01aPh

We fitted a constant (intercept-only) linear mixed model (estimated using REML
and Nelder-Mead optimizer) to predict Agency (formula: Agency ~ 1). The model
included Name as random effect (formula: ~1 | Name). The model's intercept is
at 0.50 (95% CI [0.49, 0.50], t(169994) = 177.65, p < .001).

Standardized parameters were obtained by fitting the model on a standardized
version of the dataset. 95% Confidence Intervals (CIs) and p-values were
computed using a Wald t-distribution approximation.

Report fit02aPh

We fitted a linear mixed model (estimated using REML and Nelder-Mead optimizer)
to predict Agency with Time (formula: Agency ~ Time). The model included Time
as random effects (formula: ~Time | Name). The model's total explanatory power
is weak (conditional R2 = 0.10) and the part related to the fixed effects alone
(marginal R2) is of 4.62e-04. The model's intercept, corresponding to Time = 0,
is at 0.50 (95% CI [0.49, 0.50], t(169991) = 174.88, p < .001). Within this
model:

  - The effect of Time is statistically significant and negative (beta = -0.01,
95% CI [-0.02, -5.07e-03], t(169991) = -3.88, p < .001; Std. beta = -0.02, 95%
CI [-0.03, -0.01])

Standardized parameters were obtained by fitting the model on a standardized
version of the dataset. 95% Confidence Intervals (CIs) and p-values were
computed using a Wald t-distribution approximation.

Report fit03aPh

We fitted a linear mixed model (estimated using REML and Nelder-Mead optimizer)
to predict Agency with Time and Phase (formula: Agency ~ Time * Phase). The
model included Time as random effects (formula: ~Time | Name). The model's
total explanatory power is weak (conditional R2 = 0.11) and the part related to
the fixed effects alone (marginal R2) is of 6.03e-03. The model's intercept,
corresponding to Time = 0 and Phase = BE, is at 0.53 (95% CI [0.52, 0.53],
t(169985) = 166.75, p < .001). Within this model:

  - The effect of Time is statistically significant and positive (beta = 0.04,
95% CI [0.04, 0.05], t(169985) = 12.19, p < .001; Std. beta = 0.09, 95% CI
[0.08, 0.11])
  - The effect of Phase [AE] is statistically non-significant and negative (beta
= -4.14e-03, 95% CI [-0.01, 4.04e-03], t(169985) = -0.99, p = 0.321; Std. beta
= 0.07, 95% CI [0.03, 0.12])
  - The effect of Phase [BR] is statistically significant and negative (beta =
-0.57, 95% CI [-0.63, -0.51], t(169985) = -18.56, p < .001; Std. beta = -2.51,
95% CI [-2.78, -2.24])
  - The effect of Phase [AR] is statistically non-significant and negative (beta
= -9.12e-03, 95% CI [-0.02, 5.54e-04], t(169985) = -1.85, p = 0.065; Std. beta
= -8.65e-03, 95% CI [-0.05, 0.03])
  - The effect of Time × Phase [AE] is statistically significant and negative
(beta = -0.36, 95% CI [-0.41, -0.31], t(169985) = -13.82, p < .001; Std. beta =
-0.76, 95% CI [-0.86, -0.65])
  - The effect of Time × Phase [BR] is statistically significant and positive
(beta = 1.61, 95% CI [1.42, 1.80], t(169985) = 16.65, p < .001; Std. beta =
3.40, 95% CI [3.00, 3.80])
  - The effect of Time × Phase [AR] is statistically significant and negative
(beta = -0.10, 95% CI [-0.11, -0.09], t(169985) = -13.81, p < .001; Std. beta =
-0.21, 95% CI [-0.24, -0.18])

Standardized parameters were obtained by fitting the model on a standardized
version of the dataset. 95% Confidence Intervals (CIs) and p-values were
computed using a Wald t-distribution approximation.

Report fit04aPh

We fitted a linear mixed model (estimated using REML and Nelder-Mead optimizer)
to predict Agency with Time, Phase and Outcome (formula: Agency ~ Time * Phase
* Outcome). The model included Time as random effects (formula: ~Time | Name).
The model's total explanatory power is weak (conditional R2 = 0.10) and the
part related to the fixed effects alone (marginal R2) is of 0.02. The model's
intercept, corresponding to Time = 0, Phase = BE and Outcome = loser, is at
0.52 (95% CI [0.51, 0.52], t(169977) = 115.77, p < .001). Within this model:

  - The effect of Time is statistically significant and positive (beta = 0.06,
95% CI [0.05, 0.07], t(169977) = 10.19, p < .001; Std. beta = 0.12, 95% CI
[0.10, 0.14])
  - The effect of Phase [AE] is statistically significant and negative (beta =
-0.04, 95% CI [-0.06, -0.03], t(169977) = -5.52, p < .001; Std. beta = -0.03,
95% CI [-0.11, 0.04])
  - The effect of Phase [BR] is statistically significant and negative (beta =
-0.50, 95% CI [-0.61, -0.38], t(169977) = -8.24, p < .001; Std. beta = -2.12,
95% CI [-2.65, -1.60])
  - The effect of Phase [AR] is statistically significant and negative (beta =
-0.12, 95% CI [-0.14, -0.10], t(169977) = -11.56, p < .001; Std. beta = -0.43,
95% CI [-0.51, -0.35])
  - The effect of Outcome [winner] is statistically significant and positive
(beta = 0.02, 95% CI [0.01, 0.04], t(169977) = 4.07, p < .001; Std. beta =
0.09, 95% CI [0.05, 0.13])
  - The effect of Time × Phase [AE] is statistically significant and negative
(beta = -0.49, 95% CI [-0.59, -0.39], t(169977) = -9.71, p < .001; Std. beta =
-1.04, 95% CI [-1.25, -0.83])
  - The effect of Time × Phase [BR] is statistically significant and positive
(beta = 1.15, 95% CI [0.78, 1.52], t(169977) = 6.05, p < .001; Std. beta =
2.43, 95% CI [1.64, 3.22])
  - The effect of Time × Phase [AR] is statistically significant and negative
(beta = -0.06, 95% CI [-0.09, -0.03], t(169977) = -3.82, p < .001; Std. beta =
-0.12, 95% CI [-0.19, -0.06])
  - The effect of Time × Outcome [winner] is statistically significant and
negative (beta = -0.02, 95% CI [-0.03, -6.28e-03], t(169977) = -2.83, p =
0.005; Std. beta = -0.04, 95% CI [-0.07, -0.01])
  - The effect of Phase [AE] × Outcome [winner] is statistically significant and
positive (beta = 0.06, 95% CI [0.04, 0.08], t(169977) = 6.32, p < .001; Std.
beta = 0.17, 95% CI [0.08, 0.26])
  - The effect of Phase [BR] × Outcome [winner] is statistically non-significant
and negative (beta = -0.09, 95% CI [-0.23, 0.04], t(169977) = -1.34, p = 0.179;
Std. beta = -0.50, 95% CI [-1.12, 0.11])
  - The effect of Phase [AR] × Outcome [winner] is statistically significant and
positive (beta = 0.15, 95% CI [0.12, 0.17], t(169977) = 12.55, p < .001; Std.
beta = 0.56, 95% CI [0.47, 0.65])
  - The effect of (Time × Phase [AE]) × Outcome [winner] is statistically
significant and positive (beta = 0.17, 95% CI [0.05, 0.28], t(169977) = 2.85, p
= 0.004; Std. beta = 0.35, 95% CI [0.11, 0.60])
  - The effect of (Time × Phase [BR]) × Outcome [winner] is statistically
significant and positive (beta = 0.63, 95% CI [0.19, 1.06], t(169977) = 2.83, p
= 0.005; Std. beta = 1.32, 95% CI [0.41, 2.24])
  - The effect of (Time × Phase [AR]) × Outcome [winner] is statistically
significant and negative (beta = -0.04, 95% CI [-0.08, -0.01], t(169977) =
-2.59, p = 0.010; Std. beta = -0.09, 95% CI [-0.17, -0.02])

Standardized parameters were obtained by fitting the model on a standardized
version of the dataset. 95% Confidence Intervals (CIs) and p-values were
computed using a Wald t-distribution approximation.

Save Workspace

glmmTMB Models

[1] 169997     22

[1] 495252     22

[1] 169997     22

[1] 169997     24

# A tibble: 4 × 2
  Phase Count
  <fct> <int>
1 BE    15000
2 AE    15000
3 BR    15000
4 AR    15000

Model xFit05aPhLikes

Fit

xFit05aPhLikes: [df5] LikeCount ~ Agency * Phase + (1 | Name)
 Family: truncated_poisson  ( log )
Formula:          LikeCount ~ Agency * Phase + (1 | Name)
Zero inflation:             ~Agency * Phase
Data: df5

       AIC        BIC     logLik   deviance   df.resid 
 221541905  221542058 -110770936  221541871      59983 

Random effects:

Conditional model:
 Groups Name        Variance Std.Dev.
 Name   (Intercept) 4.014    2.004   
Number of obs: 60000, groups:  Name, 847

Conditional model:
                 Estimate Std. Error z value Pr(>|z|)    
(Intercept)     4.0046334  0.0693135    57.8   <2e-16 ***
Agency         -0.1697153  0.0009258  -183.3   <2e-16 ***
PhaseAE         0.6429410  0.0006443   998.0   <2e-16 ***
PhaseBR         0.8824608  0.0006271  1407.3   <2e-16 ***
PhaseAR         0.6342543  0.0006679   949.6   <2e-16 ***
Agency:PhaseAE  0.2389858  0.0010427   229.2   <2e-16 ***
Agency:PhaseBR  0.5147667  0.0010001   514.7   <2e-16 ***
Agency:PhaseAR -0.2984013  0.0011079  -269.3   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Zero-inflation model:
                Estimate Std. Error z value Pr(>|z|)    
(Intercept)    -2.855292   0.063879  -44.70  < 2e-16 ***
Agency         -0.977835   0.118416   -8.26  < 2e-16 ***
PhaseAE        -0.113788   0.089774   -1.27    0.205    
PhaseBR        -0.414069   0.091501   -4.53 6.03e-06 ***
PhaseAR        -0.645866   0.102981   -6.27 3.57e-10 ***
Agency:PhaseAE -0.116813   0.169961   -0.69    0.492    
Agency:PhaseBR  0.003811   0.168690    0.02    0.982    
Agency:PhaseAR -0.031403   0.192888   -0.16    0.871    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--------------------------------------------------------------------- 
xFit05aPhLikes: [df5] LikeCount ~ Agency * Phase + (1 | Name)
# R2 for Mixed Models

  Conditional R2: 1.000
     Marginal R2: 0.044
--------------------------------------------------------------------- 
xFit05aPhLikes: [df5] LikeCount ~ Agency * Phase + (1 | Name)
# Intraclass Correlation Coefficient

    Adjusted ICC: 1.000
  Unadjusted ICC: 0.956
--------------------------------------------------------------------- 
xFit05aPhLikes: [df5] LikeCount ~ Agency * Phase + (1 | Name)
# ICC by Group

Group |   ICC
-------------
Name  | 1.000
--------------------------------------------------------------------- 

Effects: Agency x Phase

Compute

xFit05aPhLikes: [df5] LikeCount ~ Agency * Phase + (1 | Name)

===================================================================== 

# Average predicted counts of LikeCount

Phase: BE

Agency | Predicted |          95% CI
------------------------------------
    -3 |    641.92 | 377.87,  905.96
    -2 |    801.51 | 671.34,  931.69
    -1 |    825.26 | 788.61,  861.92
     0 |    759.30 | 754.06,  764.54
     1 |    663.30 | 660.85,  665.75
     2 |    567.26 | 564.88,  569.65
     3 |    481.15 | 478.75,  483.55

Phase: AE

Agency | Predicted |           95% CI
-------------------------------------
    -3 |    523.50 |  279.92,  767.09
    -2 |    911.71 |  748.85, 1074.56
    -1 |   1235.52 | 1180.50, 1290.54
     0 |   1452.72 | 1443.91, 1461.53
     1 |   1609.21 | 1604.20, 1614.22
     2 |   1744.24 | 1739.47, 1749.01
     3 |   1876.49 | 1871.47, 1881.51

Phase: BR

Agency | Predicted |           95% CI
-------------------------------------
    -3 |    403.89 |  271.77,  536.02
    -2 |    768.32 |  678.12,  858.53
    -1 |   1248.59 | 1210.98, 1286.19
     0 |   1869.57 | 1860.72, 1878.41
     1 |   2701.55 | 2694.24, 2708.86
     2 |   3848.66 | 3839.22, 3858.11
     3 |   5452.85 | 5440.57, 5465.13

Phase: AR

Agency | Predicted |           95% CI
-------------------------------------
    -3 |   3799.94 | 2328.29, 5271.60
    -2 |   3147.04 | 2731.52, 3562.55
    -1 |   2233.20 | 2161.09, 2305.31
     0 |   1469.78 | 1462.89, 1476.66
     1 |    937.80 |  935.39,  940.22
     2 |    591.33 |  589.68,  592.98
     3 |    371.24 |  370.01,  372.47

===================================================================== 

# (Average) Linear trend for Agency

Phase |   Slope |           95% CI |      p
-------------------------------------------
BE    |   -7.44 |  -34.92,   20.03 | 0.595 
AE    |  140.58 |  119.62,  161.53 | < .001
BR    |  545.42 |  532.83,  558.01 | < .001
AR    | -316.07 | -515.36, -116.78 | 0.003 

===================================================================== 

# (Average) Linear trend for Agency

Phase | Contrast |           95% CI |      p
--------------------------------------------
BE-AE |  -148.02 | -182.58, -113.46 | < .001
BE-BR |  -552.86 | -583.26, -522.46 | < .001
BE-AR |   308.62 |  107.44,  509.80 | 0.003 
AE-BR |  -404.84 | -429.29, -380.39 | < .001
AE-AR |   456.64 |  256.25,  657.04 | < .001
BR-AR |   861.48 |  661.80, 1061.17 | < .001

Plot: Basic

Effects: Phase

Compute

xFit05aPhLikes: [df5] LikeCount ~ Agency * Phase + (1 | Name)

===================================================================== 

# Average predicted counts of LikeCount

Phase | Predicted |           95% CI
------------------------------------
BE    |    711.61 |  709.24,  713.98
AE    |   1532.55 | 1528.18, 1536.92
BR    |   2273.83 | 2268.29, 2279.36
AR    |   1193.63 | 1190.56, 1196.71

===================================================================== 

Phase | Predicted |           95% CI |      p
---------------------------------------------
BE    |    711.61 |  709.24,  713.98 | < .001
AE    |   1532.55 | 1528.18, 1536.92 | < .001
BR    |   2273.83 | 2268.29, 2279.36 | < .001
AR    |   1193.63 | 1190.56, 1196.71 | < .001

===================================================================== 

# Pairwise comparisons

Phase | Contrast |             95% CI |      p
----------------------------------------------
BE-AE |  -820.94 |  -825.93,  -815.95 | < .001
BE-BR | -1562.21 | -1568.25, -1556.18 | < .001
BE-AR |  -482.02 |  -485.91,  -478.13 | < .001
AE-BR |  -741.27 |  -748.35,  -734.20 | < .001
AE-AR |   338.92 |   333.56,   344.28 | < .001
BR-AR |  1080.19 |  1073.84,  1086.54 | < .001

Plot: Basic

Effects: Agency

Compute

xFit05aPhLikes: [df5] LikeCount ~ Agency * Phase + (1 | Name)

===================================================================== 

# Average predicted counts of LikeCount

Agency | Predicted |           95% CI
-------------------------------------
    -3 |   1275.46 |  920.12, 1630.79
    -2 |   1369.84 | 1256.37, 1483.31
    -1 |   1390.49 | 1364.03, 1416.95
     0 |   1436.86 | 1432.83, 1440.90
     1 |   1572.57 | 1569.97, 1575.18
     2 |   1833.39 | 1830.35, 1836.43
     3 |   2252.68 | 2248.90, 2256.46

===================================================================== 

# (Average) Linear trend for Agency

Slope  |         95% CI |      p
--------------------------------
138.34 | 132.78, 143.90 | < .001

===================================================================== 

# (Average) Linear trend for Agency

Slope  |         95% CI |      p
--------------------------------
138.34 | 132.78, 143.90 | < .001

Plot: Basic

Model xFit06aPhRetweets

Fit

xFit06aPhRetweets: [df5] RetweetCount ~ Agency * Phase + (1 | Name)
 Family: truncated_poisson  ( log )
Formula:          RetweetCount ~ Agency * Phase + (1 | Name)
Zero inflation:                ~Agency * Phase
Data: df5

      AIC       BIC    logLik  deviance  df.resid 
 38582668  38582821 -19291317  38582634     59983 

Random effects:

Conditional model:
 Groups Name        Variance Std.Dev.
 Name   (Intercept) 3.22     1.794   
Number of obs: 60000, groups:  Name, 847

Conditional model:
                Estimate Std. Error z value Pr(>|z|)    
(Intercept)     3.052772   0.062654    48.7   <2e-16 ***
Agency         -0.291141   0.001850  -157.3   <2e-16 ***
PhaseAE         0.085968   0.001370    62.8   <2e-16 ***
PhaseBR         0.416608   0.001290   322.8   <2e-16 ***
PhaseAR         0.280408   0.001376   203.8   <2e-16 ***
Agency:PhaseAE  0.382094   0.002232   171.2   <2e-16 ***
Agency:PhaseBR  0.543501   0.002082   261.0   <2e-16 ***
Agency:PhaseAR -0.248806   0.002340  -106.3   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Zero-inflation model:
               Estimate Std. Error z value Pr(>|z|)    
(Intercept)    -2.50996    0.05547  -45.25  < 2e-16 ***
Agency         -0.65152    0.09842   -6.62  3.6e-11 ***
PhaseAE         0.22469    0.07317    3.07 0.002133 ** 
PhaseBR         0.09407    0.07190    1.31 0.190749    
PhaseAR        -0.08184    0.07733   -1.06 0.289903    
Agency:PhaseAE -0.44233    0.13470   -3.28 0.001024 ** 
Agency:PhaseBR -0.32139    0.12936   -2.48 0.012977 *  
Agency:PhaseAR -0.53423    0.14284   -3.74 0.000184 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--------------------------------------------------------------------- 
xFit06aPhRetweets: [df5] RetweetCount ~ Agency * Phase + (1 | Name)
# R2 for Mixed Models

  Conditional R2: 1.000
     Marginal R2: 0.024
--------------------------------------------------------------------- 
xFit06aPhRetweets: [df5] RetweetCount ~ Agency * Phase + (1 | Name)
# Intraclass Correlation Coefficient

    Adjusted ICC: 1.000
  Unadjusted ICC: 0.976
--------------------------------------------------------------------- 
xFit06aPhRetweets: [df5] RetweetCount ~ Agency * Phase + (1 | Name)
# ICC by Group

Group |   ICC
-------------
Name  | 1.000
--------------------------------------------------------------------- 

Effects: Agency x Phase

Compute

xFit06aPhRetweets: [df5] RetweetCount ~ Agency * Phase + (1 | Name)

===================================================================== 

# Average predicted counts of RetweetCount

Phase: BE

Agency | Predicted |         95% CI
-----------------------------------
    -3 |    325.22 | 246.14, 404.30
    -2 |    294.48 | 262.20, 326.77
    -1 |    247.37 | 237.77, 256.98
     0 |    197.67 | 196.00, 199.33
     1 |    153.27 | 152.39, 154.15
     2 |    116.86 | 115.83, 117.89
     3 |     88.29 |  87.33,  89.25

Phase: AE

Agency | Predicted |         95% CI
-----------------------------------
    -3 |     47.81 |  26.54,  69.09
    -2 |    101.82 |  80.97, 122.68
    -1 |    163.11 | 153.44, 172.79
     0 |    211.40 | 209.55, 213.26
     1 |    246.68 | 245.53, 247.82
     2 |    276.22 | 274.81, 277.62
     3 |    304.80 | 302.84, 306.76

Phase: BR

Agency | Predicted |         95% CI
-----------------------------------
    -3 |     57.31 |  37.51,  77.12
    -2 |    120.44 | 102.29, 138.59
    -1 |    203.74 | 194.70, 212.78
     0 |    297.59 | 295.37, 299.81
     1 |    403.59 | 401.84, 405.34
     2 |    530.20 | 527.81, 532.60
     3 |    687.79 | 684.26, 691.31

Phase: AR

Agency | Predicted |         95% CI
-----------------------------------
    -3 |    394.14 | 198.99, 589.30
    -2 |    462.13 | 362.80, 561.46
    -1 |    389.84 | 367.96, 411.72
     0 |    263.18 | 261.20, 265.16
     1 |    161.20 | 160.56, 161.84
     2 |     95.48 |  94.99,  95.97
     3 |     56.00 |  55.59,  56.42

===================================================================== 

# (Average) Linear trend for Agency

Phase |  Slope |         95% CI |      p
----------------------------------------
BE    | -23.03 | -33.09, -12.97 | < .001
AE    |  26.27 |  24.65,  27.88 | < .001
BR    |  67.28 |  65.59,  68.98 | < .001
AR    | -25.57 | -45.02,  -6.11 | 0.010 

===================================================================== 

# (Average) Linear trend for Agency

Phase | Contrast |          95% CI |      p
-------------------------------------------
BE-AE |   -49.30 |  -59.48, -39.11 | < .001
BE-BR |   -90.32 | -100.52, -80.12 | < .001
BE-AR |     2.54 |  -19.37,  24.44 | 0.821 
AE-BR |   -41.02 |  -43.36, -38.68 | < .001
AE-AR |    51.83 |   32.31,  71.36 | < .001
BR-AR |    92.85 |   73.32, 112.38 | < .001

Plot: Basic

Effects: Phase

Compute

xFit06aPhRetweets: [df5] RetweetCount ~ Agency * Phase + (1 | Name)

===================================================================== 

# Average predicted counts of RetweetCount

Phase | Predicted |         95% CI
----------------------------------
BE    |    175.12 | 174.36, 175.88
AE    |    229.45 | 228.53, 230.38
BR    |    349.82 | 348.49, 351.14
AR    |    210.27 | 209.41, 211.13

===================================================================== 

Phase | Predicted |         95% CI |      p
-------------------------------------------
BE    |    175.12 | 174.36, 175.88 | < .001
AE    |    229.45 | 228.53, 230.38 | < .001
BR    |    349.82 | 348.49, 351.14 | < .001
AR    |    210.27 | 209.41, 211.13 | < .001

===================================================================== 

# Pairwise comparisons

Phase | Contrast |           95% CI |      p
--------------------------------------------
BE-AE |   -54.34 |  -55.54,  -53.13 | < .001
BE-BR |  -174.70 | -176.23, -173.16 | < .001
BE-AR |   -35.15 |  -36.30,  -33.99 | < .001
AE-BR |  -120.36 | -121.99, -118.73 | < .001
AE-AR |    19.19 |   17.91,   20.46 | < .001
BR-AR |   139.55 |  137.96,  141.14 | < .001

Plot: Basic

Effects: Agency

Compute

xFit06aPhRetweets: [df5] RetweetCount ~ Agency * Phase + (1 | Name)

===================================================================== 

# Average predicted counts of RetweetCount

Agency | Predicted |         95% CI
-----------------------------------
    -3 |    187.09 | 137.74, 236.44
    -2 |    230.25 | 204.71, 255.78
    -1 |    244.82 | 238.16, 251.48
     0 |    245.36 | 244.37, 246.36
     1 |    252.55 | 251.92, 253.18
     2 |    274.10 | 273.28, 274.92
     3 |    311.92 | 310.75, 313.08

===================================================================== 

# (Average) Linear trend for Agency

Slope |     95% CI |      p
---------------------------
7.47  | 6.10, 8.83 | < .001

===================================================================== 

# (Average) Linear trend for Agency

Slope |     95% CI |      p
---------------------------
7.47  | 6.10, 8.83 | < .001

Plot: Basic

Model xFit05xPhLikes (+Outcome)

Fit

xFit05xPhLikes: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)
 Family: truncated_poisson  ( log )
Formula:          LikeCount ~ Agency * Phase * Outcome + (1 | Name)
Zero inflation:             ~Agency * Phase * Outcome
Data: df5

       AIC        BIC     logLik   deviance   df.resid 
 220099606  220099903 -110049770  220099540      59967 

Random effects:

Conditional model:
 Groups Name        Variance Std.Dev.
 Name   (Intercept) 3.629    1.905   
Number of obs: 60000, groups:  Name, 847

Conditional model:
                              Estimate Std. Error z value Pr(>|z|)    
(Intercept)                   3.403578   0.101509    33.5  < 2e-16 ***
Agency                       -0.236854   0.001846  -128.3  < 2e-16 ***
PhaseAE                       0.558708   0.001422   392.8  < 2e-16 ***
PhaseBR                       0.221862   0.001379   160.9  < 2e-16 ***
PhaseAR                       0.478180   0.001411   338.8  < 2e-16 ***
Outcomewinner                 1.080198   0.133490     8.1 5.87e-16 ***
Agency:PhaseAE                0.618810   0.002383   259.6  < 2e-16 ***
Agency:PhaseBR                0.539332   0.002324   232.1  < 2e-16 ***
Agency:PhaseAR                0.335215   0.002474   135.5  < 2e-16 ***
Agency:Outcomewinner          0.109045   0.002136    51.1  < 2e-16 ***
PhaseAE:Outcomewinner         0.138890   0.001603    86.6  < 2e-16 ***
PhaseBR:Outcomewinner         0.804573   0.001557   516.8  < 2e-16 ***
PhaseAR:Outcomewinner         0.214589   0.001607   133.5  < 2e-16 ***
Agency:PhaseAE:Outcomewinner -0.438193   0.002663  -164.6  < 2e-16 ***
Agency:PhaseBR:Outcomewinner -0.100292   0.002590   -38.7  < 2e-16 ***
Agency:PhaseAR:Outcomewinner -0.728943   0.002776  -262.6  < 2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Zero-inflation model:
                             Estimate Std. Error z value Pr(>|z|)    
(Intercept)                  -2.30979    0.07459 -30.965  < 2e-16 ***
Agency                       -1.07909    0.14241  -7.577 3.52e-14 ***
PhaseAE                       0.19645    0.10517   1.868 0.061768 .  
PhaseBR                      -0.09359    0.10420  -0.898 0.369091    
PhaseAR                      -0.12255    0.11572  -1.059 0.289585    
Outcomewinner                -1.36634    0.14790  -9.238  < 2e-16 ***
Agency:PhaseAE                0.59738    0.20263   2.948 0.003197 ** 
Agency:PhaseBR                0.64089    0.19918   3.218 0.001293 ** 
Agency:PhaseAR                0.57939    0.22953   2.524 0.011595 *  
Agency:Outcomewinner          0.62314    0.26113   2.386 0.017018 *  
PhaseAE:Outcomewinner        -0.48279    0.20876  -2.313 0.020741 *  
PhaseBR:Outcomewinner        -1.02919    0.24455  -4.209 2.57e-05 ***
PhaseAR:Outcomewinner        -1.22436    0.26595  -4.604 4.15e-06 ***
Agency:PhaseAE:Outcomewinner -1.30315    0.38436  -3.390 0.000698 ***
Agency:PhaseBR:Outcomewinner -1.02597    0.43229  -2.373 0.017629 *  
Agency:PhaseAR:Outcomewinner  0.03282    0.44608   0.074 0.941354    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--------------------------------------------------------------------- 
xFit05xPhLikes: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)
# R2 for Mixed Models

  Conditional R2: 1.000
     Marginal R2: 0.135
--------------------------------------------------------------------- 
xFit05xPhLikes: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)
# Intraclass Correlation Coefficient

    Adjusted ICC: 1.000
  Unadjusted ICC: 0.864
--------------------------------------------------------------------- 
xFit05xPhLikes: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)
# ICC by Group

Group |   ICC
-------------
Name  | 1.000
--------------------------------------------------------------------- 

Effects: Agency x Outcome x Phase

Compute

xFit05xPhLikes: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)

===================================================================== 

# Average predicted counts of LikeCount

Outcome: loser
Phase: BE

Agency | Predicted |           95% CI
-------------------------------------
    -3 |    201.04 |  61.15,   340.92
    -2 |    301.03 | 195.73,   406.33
    -1 |    341.83 | 277.56,   406.10
     0 |    317.06 | 264.40,   369.72
     1 |    266.07 | 221.99,   310.15
     2 |    214.60 | 179.05,   250.15
     3 |    170.64 | 142.37,   198.92

Outcome: loser
Phase: AE

Agency | Predicted |            95% CI
--------------------------------------
    -3 |    128.12 |   81.78,   174.45
    -2 |    215.61 |  165.83,   265.40
    -1 |    347.87 |  286.07,   409.67
     0 |    543.67 |  453.24,   634.09
     1 |    830.78 |  692.64,   968.92
     2 |   1250.42 | 1041.59,  1459.25
     3 |   1863.44 | 1552.08,  2174.79

Outcome: loser
Phase: BR

Agency | Predicted |           95% CI
-------------------------------------
    -3 |    131.41 |  94.21,   168.60
    -2 |    195.24 | 155.93,   234.54
    -1 |    282.03 | 233.54,   330.51
     0 |    399.03 | 332.79,   465.26
     1 |    556.32 | 463.96,   648.69
     2 |    767.83 | 639.96,   895.70
     3 |   1052.57 | 877.14,  1228.01

Outcome: loser
Phase: AR

Agency | Predicted |           95% CI
-------------------------------------
    -3 |    300.42 | 189.72,   411.11
    -2 |    372.86 | 287.65,   458.06
    -1 |    445.11 | 366.72,   523.50
     0 |    516.82 | 430.94,   602.70
     1 |    588.94 | 491.03,   686.85
     2 |    663.01 | 552.41,   773.60
     3 |    740.65 | 617.08,   864.23

Outcome: winner
Phase: BE

Agency | Predicted |            95% CI
--------------------------------------
    -3 |   1369.93 | 1142.44,  1597.43
    -2 |   1246.86 | 1103.20,  1390.52
    -1 |   1121.62 | 1010.27,  1232.96
     0 |   1001.13 |  904.77,  1097.49
     1 |    889.06 |  803.57,   974.54
     2 |    786.94 |  711.13,   862.76
     3 |    695.09 |  628.05,   762.13

Outcome: winner
Phase: AE

Agency | Predicted |            95% CI
--------------------------------------
    -3 |   1086.11 |  407.69,  1764.54
    -2 |   1553.74 | 1229.15,  1878.32
    -1 |   1843.99 | 1653.02,  2034.95
     0 |   2023.62 | 1829.03,  2218.22
     1 |   2161.07 | 1953.45,  2368.68
     2 |   2287.55 | 2067.78,  2507.32
     3 |   2414.68 | 2182.67,  2646.70

Outcome: winner
Phase: BR

Agency | Predicted |            95% CI
--------------------------------------
    -3 |   1021.33 |  797.64,  1245.01
    -2 |   1472.20 | 1302.50,  1641.90
    -1 |   2059.39 | 1858.55,  2260.23
     0 |   2841.58 | 2568.52,  3114.63
     1 |   3897.16 | 3522.79,  4271.53
     2 |   5330.76 | 4818.65,  5842.87
     3 |   7283.38 | 6583.64,  7983.12

Outcome: winner
Phase: AR

Agency | Predicted |            95% CI
--------------------------------------
    -3 |   9770.76 | 8827.19, 10714.34
    -2 |   5795.98 | 5237.25,  6354.70
    -1 |   3437.75 | 3106.96,  3768.54
     0 |   2038.75 | 1842.85,  2234.64
     1 |   1208.88 | 1092.72,  1325.04
     2 |    716.68 |  647.58,   785.78
     3 |    424.80 |  383.42,   466.17

===================================================================== 

# (Average) Linear trend for Agency

Outcome | Phase |    Slope |             95% CI |      p
--------------------------------------------------------
loser   |    BE |     0.34 |   -12.53,    13.21 | 0.959 
loser   |    AE |   207.36 |   176.49,   238.24 | < .001
loser   |    BR |   107.53 |    91.27,   123.78 | < .001
loser   |    AR |    49.60 |    34.97,    64.23 | < .001
winner  |    BE |   -74.49 |  -101.95,   -47.03 | < .001
winner  |    AE |   160.46 |    79.70,   241.21 | < .001
winner  |    BR |   734.46 |   643.30,   825.62 | < .001
winner  |    AR | -1173.57 | -1313.32, -1033.82 | < .001

===================================================================== 

# (Average) Linear trend for Agency

Outcome       | Phase | Contrast |           95% CI |      p
------------------------------------------------------------
loser-loser   | BE-AE |  -207.03 | -240.43, -173.62 | < .001
loser-loser   | BE-BR |  -107.19 | -127.89,  -86.48 | < .001
loser-loser   | BE-AR |   -49.26 |  -68.73,  -29.79 | < .001
loser-winner  | BE-BE |    74.83 |   44.52,  105.14 | < .001
loser-winner  | BE-AE |  -160.12 | -241.90,  -78.33 | < .001
loser-winner  | BE-BR |  -734.12 | -826.22, -642.01 | < .001
loser-winner  | BE-AR |  1173.91 | 1033.60, 1314.22 | < .001
loser-loser   | AE-BR |    99.84 |   82.39,  117.29 | < .001
loser-loser   | AE-AR |   157.77 |  130.45,  185.08 | < .001
loser-winner  | AE-BE |   281.86 |  247.46,  316.25 | < .001
loser-winner  | AE-AE |    46.91 |  -45.85,  139.67 | 0.322 
loser-winner  | AE-BR |  -527.09 | -647.23, -406.96 | < .001
loser-winner  | AE-AR |  1380.94 | 1270.35, 1491.52 | < .001
loser-loser   | BR-AR |    57.93 |   41.81,   74.05 | < .001
loser-winner  | BR-BE |   182.02 |  154.70,  209.34 | < .001
loser-winner  | BR-AE |   -52.93 | -138.79,   32.93 | 0.235 
loser-winner  | BR-BR |  -626.93 | -733.02, -520.84 | < .001
loser-winner  | BR-AR |  1281.10 | 1156.54, 1405.65 | < .001
loser-winner  | AR-BE |   124.09 |   95.06,  153.12 | < .001
loser-winner  | AR-AE |  -110.86 | -194.56,  -27.15 | 0.010 
loser-winner  | AR-BR |  -684.86 | -783.65, -586.06 | < .001
loser-winner  | AR-AR |  1223.17 | 1089.89, 1356.46 | < .001
winner-winner | BE-AE |  -234.95 | -322.20, -147.70 | < .001
winner-winner | BE-BR |  -808.95 | -911.92, -705.97 | < .001
winner-winner | BE-AR |  1099.08 |  965.61, 1232.55 | < .001
winner-winner | AE-BR |  -574.00 | -681.31, -466.69 | < .001
winner-winner | AE-AR |  1334.03 | 1156.97, 1511.08 | < .001
winner-winner | BR-AR |  1908.03 | 1679.82, 2136.24 | < .001

Plot: Basic

Effects: Phase x Outcome

Compute

xFit05xPhLikes: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)

===================================================================== 

# Average predicted counts of LikeCount

Outcome: loser

Phase | Predicted |           95% CI
------------------------------------
BE    |    293.00 |  244.73,  341.26
AE    |    675.67 |  561.96,  789.37
BR    |    471.96 |  392.83,  551.09
AR    |    551.20 |  459.36,  643.03

Outcome: winner

Phase | Predicted |           95% CI
------------------------------------
BE    |    947.18 |  855.53, 1038.83
AE    |   2090.05 | 1890.03, 2290.06
BR    |   3330.59 | 3016.62, 3644.56
AR    |   1623.61 | 1462.93, 1784.29

===================================================================== 

Phase | Outcome | Predicted |           95% CI |      p
-------------------------------------------------------
BE    |   loser |    293.00 |  244.73,  341.26 | < .001
AE    |   loser |    675.67 |  561.96,  789.37 | < .001
BR    |   loser |    471.96 |  392.83,  551.09 | < .001
AR    |   loser |    551.20 |  459.36,  643.03 | < .001
BE    |  winner |    947.18 |  855.53, 1038.83 | < .001
AE    |  winner |   2090.05 | 1890.03, 2290.06 | < .001
BR    |  winner |   3330.59 | 3016.62, 3644.56 | < .001
AR    |  winner |   1623.61 | 1462.93, 1784.29 | < .001

===================================================================== 

# Pairwise comparisons

Phase |       Outcome | Contrast |             95% CI |      p
--------------------------------------------------------------
BE-AE |   loser-loser |  -382.67 |  -448.34,  -317.00 | < .001
BE-BR |   loser-loser |  -178.96 |  -210.09,  -147.84 | < .001
BE-AR |   loser-loser |  -258.20 |  -302.04,  -214.36 | < .001
BE-BE |  loser-winner |  -654.18 |  -794.06,  -514.31 | < .001
BE-AE |  loser-winner | -1797.05 | -2045.29, -1548.81 | < .001
BE-BR |  loser-winner | -3037.60 | -3399.79, -2675.40 | < .001
BE-AR |  loser-winner | -1330.62 | -1539.52, -1121.71 | < .001
AE-BR |   loser-loser |   203.71 |   168.33,   239.08 | < .001
AE-AR |   loser-loser |   124.47 |   100.92,   148.01 | < .001
AE-BE |  loser-winner |  -271.51 |  -476.75,   -66.27 | 0.010 
AE-AE |  loser-winner | -1414.38 | -1727.95, -1100.81 | < .001
AE-BR |  loser-winner | -2654.93 | -3082.44, -2227.41 | < .001
AE-AR |  loser-winner |  -947.95 | -1222.20,  -673.69 | < .001
BR-AR |   loser-loser |   -79.24 |   -93.57,   -64.90 | < .001
BR-BE |  loser-winner |  -475.22 |  -645.92,  -304.52 | < .001
BR-AE |  loser-winner | -1618.09 | -1897.15, -1339.03 | < .001
BR-BR |  loser-winner | -2858.63 | -3251.65, -2465.62 | < .001
BR-AR |  loser-winner | -1151.65 | -1391.39,  -911.92 | < .001
AR-BE |  loser-winner |  -395.98 |  -579.36,  -212.61 | < .001
AR-AE |  loser-winner | -1538.85 | -1830.57, -1247.13 | < .001
AR-BR |  loser-winner | -2779.40 | -3185.06, -2373.73 | < .001
AR-AR |  loser-winner | -1072.42 | -1324.82,  -820.02 | < .001
BE-AE | winner-winner | -1142.87 | -1251.37, -1034.37 | < .001
BE-BR | winner-winner | -2383.41 | -2605.82, -2161.01 | < .001
BE-AR | winner-winner |  -676.43 |  -745.61,  -607.26 | < .001
AE-BR | winner-winner | -1240.55 | -1354.71, -1126.38 | < .001
AE-AR | winner-winner |   466.43 |   426.78,   506.09 | < .001
BR-AR | winner-winner |  1706.98 |  1553.60,  1860.36 | < .001

Plot: Basic

Effects: Agency x Phase

Compute

xFit05xPhLikes: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)

===================================================================== 

# Average predicted counts of LikeCount

Phase: BE

Agency | Predicted |          95% CI
------------------------------------
    -3 |    940.79 | 813.19, 1068.40
    -2 |    899.62 | 838.94,  960.29
    -1 |    835.33 | 814.31,  856.36
     0 |    749.99 | 745.70,  754.28
     1 |    660.34 | 657.71,  662.96
     2 |    576.82 | 573.02,  580.61
     3 |    502.55 | 498.62,  506.47

Phase: AE

Agency | Predicted |           95% CI
-------------------------------------
    -3 |    734.40 |  309.89, 1158.92
    -2 |   1062.47 |  879.60, 1245.34
    -1 |   1294.72 | 1248.78, 1340.65
     0 |   1480.29 | 1473.50, 1487.07
     1 |   1672.68 | 1667.18, 1678.17
     2 |   1906.79 | 1896.31, 1917.26
     3 |   2212.30 | 2196.46, 2228.15

Phase: BR

Agency | Predicted |           95% CI
-------------------------------------
    -3 |    694.61 |  566.90,  822.31
    -2 |   1003.39 |  943.44, 1063.33
    -1 |   1406.87 | 1384.31, 1429.42
     0 |   1944.84 | 1939.27, 1950.41
     1 |   2670.63 | 2665.84, 2675.42
     2 |   3655.56 | 3647.34, 3663.79
     3 |   4995.85 | 4983.38, 5008.33

Phase: AR

Agency | Predicted |           95% CI
-------------------------------------
    -3 |   6293.90 | 6221.99, 6365.80
    -2 |   3804.98 | 3767.93, 3842.03
    -1 |   2339.06 | 2323.11, 2355.01
     0 |   1480.00 | 1475.61, 1484.39
     1 |    981.28 |  977.40,  985.17
     2 |    696.97 |  690.73,  703.22
     3 |    540.76 |  533.67,  547.84

===================================================================== 

# (Average) Linear trend for Agency

Phase |  Slope |         95% CI |      p
----------------------------------------
BE    |   0.34 | -12.53,  13.21 | 0.959 
AE    | 207.36 | 176.49, 238.24 | < .001
BR    | 107.53 |  91.27, 123.78 | < .001
AR    |  49.60 |  34.97,  64.23 | < .001

===================================================================== 

# (Average) Linear trend for Agency

Phase | Contrast |           95% CI |      p
--------------------------------------------
BE-AE |  -207.03 | -240.43, -173.62 | < .001
BE-BR |  -107.19 | -127.89,  -86.48 | < .001
BE-AR |   -49.26 |  -68.73,  -29.79 | < .001
AE-BR |    99.84 |   82.39,  117.29 | < .001
AE-AR |   157.77 |  130.45,  185.08 | < .001
BR-AR |    57.93 |   41.81,   74.05 | < .001

Plot: Basic

Effects: Phase

Compute

xFit05xPhLikes: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)

===================================================================== 

# Average predicted counts of LikeCount

Phase | Predicted |           95% CI
------------------------------------
BE    |    705.67 |  703.64,  707.71
AE    |   1567.55 | 1563.90, 1571.19
BR    |   2300.50 | 2297.19, 2303.81
AR    |   1210.33 | 1207.77, 1212.89

===================================================================== 

Phase | Predicted |           95% CI |      p
---------------------------------------------
BE    |    705.67 |  703.64,  707.71 | < .001
AE    |   1567.55 | 1563.90, 1571.19 | < .001
BR    |   2300.50 | 2297.19, 2303.81 | < .001
AR    |   1210.33 | 1207.77, 1212.89 | < .001

===================================================================== 

# Pairwise comparisons

Phase | Contrast |             95% CI |      p
----------------------------------------------
BE-AE |  -861.87 |  -866.06,  -857.69 | < .001
BE-BR | -1594.83 | -1598.73, -1590.92 | < .001
BE-AR |  -504.66 |  -507.94,  -501.38 | < .001
AE-BR |  -732.95 |  -737.91,  -728.00 | < .001
AE-AR |   357.21 |   352.74,   361.69 | < .001
BR-AR |  1090.17 |  1085.95,  1094.38 | < .001

Plot: Basic

Effects: Agency

Compute

xFit05xPhLikes: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)

===================================================================== 

# Average predicted counts of LikeCount

Agency | Predicted |           95% CI
-------------------------------------
    -3 |   2097.24 | 1958.79, 2235.70
    -2 |   1679.69 | 1618.88, 1740.49
    -1 |   1495.51 | 1479.04, 1511.97
     0 |   1469.94 | 1467.14, 1472.73
     1 |   1579.21 | 1577.17, 1581.25
     2 |   1820.50 | 1817.07, 1823.92
     3 |   2207.40 | 2202.46, 2212.34

===================================================================== 

# (Average) Linear trend for Agency

Slope  |         95% CI |      p
--------------------------------
110.86 | 106.83, 114.90 | < .001

===================================================================== 

# (Average) Linear trend for Agency

Slope  |         95% CI |      p
--------------------------------
110.86 | 106.83, 114.90 | < .001

Plot: Basic

Model xFit06xPhRetweets (+Outcome)

Fit

xFit06xPhRetweets: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)
 Family: truncated_poisson  ( log )
Formula:          LikeCount ~ Agency * Phase * Outcome + (1 | Name)
Zero inflation:             ~Agency * Phase * Outcome
Data: df5

       AIC        BIC     logLik   deviance   df.resid 
 220099606  220099903 -110049770  220099540      59967 

Random effects:

Conditional model:
 Groups Name        Variance Std.Dev.
 Name   (Intercept) 3.629    1.905   
Number of obs: 60000, groups:  Name, 847

Conditional model:
                              Estimate Std. Error z value Pr(>|z|)    
(Intercept)                   3.403578   0.101509    33.5  < 2e-16 ***
Agency                       -0.236854   0.001846  -128.3  < 2e-16 ***
PhaseAE                       0.558708   0.001422   392.8  < 2e-16 ***
PhaseBR                       0.221862   0.001379   160.9  < 2e-16 ***
PhaseAR                       0.478180   0.001411   338.8  < 2e-16 ***
Outcomewinner                 1.080198   0.133490     8.1 5.87e-16 ***
Agency:PhaseAE                0.618810   0.002383   259.6  < 2e-16 ***
Agency:PhaseBR                0.539332   0.002324   232.1  < 2e-16 ***
Agency:PhaseAR                0.335215   0.002474   135.5  < 2e-16 ***
Agency:Outcomewinner          0.109045   0.002136    51.1  < 2e-16 ***
PhaseAE:Outcomewinner         0.138890   0.001603    86.6  < 2e-16 ***
PhaseBR:Outcomewinner         0.804573   0.001557   516.8  < 2e-16 ***
PhaseAR:Outcomewinner         0.214589   0.001607   133.5  < 2e-16 ***
Agency:PhaseAE:Outcomewinner -0.438193   0.002663  -164.6  < 2e-16 ***
Agency:PhaseBR:Outcomewinner -0.100292   0.002590   -38.7  < 2e-16 ***
Agency:PhaseAR:Outcomewinner -0.728943   0.002776  -262.6  < 2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Zero-inflation model:
                             Estimate Std. Error z value Pr(>|z|)    
(Intercept)                  -2.30979    0.07459 -30.965  < 2e-16 ***
Agency                       -1.07909    0.14241  -7.577 3.52e-14 ***
PhaseAE                       0.19645    0.10517   1.868 0.061768 .  
PhaseBR                      -0.09359    0.10420  -0.898 0.369091    
PhaseAR                      -0.12255    0.11572  -1.059 0.289585    
Outcomewinner                -1.36634    0.14790  -9.238  < 2e-16 ***
Agency:PhaseAE                0.59738    0.20263   2.948 0.003197 ** 
Agency:PhaseBR                0.64089    0.19918   3.218 0.001293 ** 
Agency:PhaseAR                0.57939    0.22953   2.524 0.011595 *  
Agency:Outcomewinner          0.62314    0.26113   2.386 0.017018 *  
PhaseAE:Outcomewinner        -0.48279    0.20876  -2.313 0.020741 *  
PhaseBR:Outcomewinner        -1.02919    0.24455  -4.209 2.57e-05 ***
PhaseAR:Outcomewinner        -1.22436    0.26595  -4.604 4.15e-06 ***
Agency:PhaseAE:Outcomewinner -1.30315    0.38436  -3.390 0.000698 ***
Agency:PhaseBR:Outcomewinner -1.02597    0.43229  -2.373 0.017629 *  
Agency:PhaseAR:Outcomewinner  0.03282    0.44608   0.074 0.941354    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--------------------------------------------------------------------- 
xFit06xPhRetweets: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)
# R2 for Mixed Models

  Conditional R2: 1.000
     Marginal R2: 0.135
--------------------------------------------------------------------- 
xFit06xPhRetweets: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)
# Intraclass Correlation Coefficient

    Adjusted ICC: 1.000
  Unadjusted ICC: 0.864
--------------------------------------------------------------------- 
xFit06xPhRetweets: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)
# ICC by Group

Group |   ICC
-------------
Name  | 1.000
--------------------------------------------------------------------- 

Effects: Agency x Outcome x Phase

Compute

xFit06xPhRetweets: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)

===================================================================== 

# Average predicted counts of LikeCount

Outcome: loser
Phase: BE

Agency | Predicted |           95% CI
-------------------------------------
    -3 |    201.04 |  61.15,   340.92
    -2 |    301.03 | 195.73,   406.33
    -1 |    341.83 | 277.56,   406.10
     0 |    317.06 | 264.40,   369.72
     1 |    266.07 | 221.99,   310.15
     2 |    214.60 | 179.05,   250.15
     3 |    170.64 | 142.37,   198.92

Outcome: loser
Phase: AE

Agency | Predicted |            95% CI
--------------------------------------
    -3 |    128.12 |   81.78,   174.45
    -2 |    215.61 |  165.83,   265.40
    -1 |    347.87 |  286.07,   409.67
     0 |    543.67 |  453.24,   634.09
     1 |    830.78 |  692.64,   968.92
     2 |   1250.42 | 1041.59,  1459.25
     3 |   1863.44 | 1552.08,  2174.79

Outcome: loser
Phase: BR

Agency | Predicted |           95% CI
-------------------------------------
    -3 |    131.41 |  94.21,   168.60
    -2 |    195.24 | 155.93,   234.54
    -1 |    282.03 | 233.54,   330.51
     0 |    399.03 | 332.79,   465.26
     1 |    556.32 | 463.96,   648.69
     2 |    767.83 | 639.96,   895.70
     3 |   1052.57 | 877.14,  1228.01

Outcome: loser
Phase: AR

Agency | Predicted |           95% CI
-------------------------------------
    -3 |    300.42 | 189.72,   411.11
    -2 |    372.86 | 287.65,   458.06
    -1 |    445.11 | 366.72,   523.50
     0 |    516.82 | 430.94,   602.70
     1 |    588.94 | 491.03,   686.85
     2 |    663.01 | 552.41,   773.60
     3 |    740.65 | 617.08,   864.23

Outcome: winner
Phase: BE

Agency | Predicted |            95% CI
--------------------------------------
    -3 |   1369.93 | 1142.44,  1597.43
    -2 |   1246.86 | 1103.20,  1390.52
    -1 |   1121.62 | 1010.27,  1232.96
     0 |   1001.13 |  904.77,  1097.49
     1 |    889.06 |  803.57,   974.54
     2 |    786.94 |  711.13,   862.76
     3 |    695.09 |  628.05,   762.13

Outcome: winner
Phase: AE

Agency | Predicted |            95% CI
--------------------------------------
    -3 |   1086.11 |  407.69,  1764.54
    -2 |   1553.74 | 1229.15,  1878.32
    -1 |   1843.99 | 1653.02,  2034.95
     0 |   2023.62 | 1829.03,  2218.22
     1 |   2161.07 | 1953.45,  2368.68
     2 |   2287.55 | 2067.78,  2507.32
     3 |   2414.68 | 2182.67,  2646.70

Outcome: winner
Phase: BR

Agency | Predicted |            95% CI
--------------------------------------
    -3 |   1021.33 |  797.64,  1245.01
    -2 |   1472.20 | 1302.50,  1641.90
    -1 |   2059.39 | 1858.55,  2260.23
     0 |   2841.58 | 2568.52,  3114.63
     1 |   3897.16 | 3522.79,  4271.53
     2 |   5330.76 | 4818.65,  5842.87
     3 |   7283.38 | 6583.64,  7983.12

Outcome: winner
Phase: AR

Agency | Predicted |            95% CI
--------------------------------------
    -3 |   9770.76 | 8827.19, 10714.34
    -2 |   5795.98 | 5237.25,  6354.70
    -1 |   3437.75 | 3106.96,  3768.54
     0 |   2038.75 | 1842.85,  2234.64
     1 |   1208.88 | 1092.72,  1325.04
     2 |    716.68 |  647.58,   785.78
     3 |    424.80 |  383.42,   466.17

===================================================================== 

# (Average) Linear trend for Agency

Outcome | Phase |    Slope |             95% CI |      p
--------------------------------------------------------
loser   |    BE |     0.34 |   -12.53,    13.21 | 0.959 
loser   |    AE |   207.36 |   176.49,   238.24 | < .001
loser   |    BR |   107.53 |    91.27,   123.78 | < .001
loser   |    AR |    49.60 |    34.97,    64.23 | < .001
winner  |    BE |   -74.49 |  -101.95,   -47.03 | < .001
winner  |    AE |   160.46 |    79.70,   241.21 | < .001
winner  |    BR |   734.46 |   643.30,   825.62 | < .001
winner  |    AR | -1173.57 | -1313.32, -1033.82 | < .001

===================================================================== 

# (Average) Linear trend for Agency

Outcome       | Phase | Contrast |           95% CI |      p
------------------------------------------------------------
loser-loser   | BE-AE |  -207.03 | -240.43, -173.62 | < .001
loser-loser   | BE-BR |  -107.19 | -127.89,  -86.48 | < .001
loser-loser   | BE-AR |   -49.26 |  -68.73,  -29.79 | < .001
loser-winner  | BE-BE |    74.83 |   44.52,  105.14 | < .001
loser-winner  | BE-AE |  -160.12 | -241.90,  -78.33 | < .001
loser-winner  | BE-BR |  -734.12 | -826.22, -642.01 | < .001
loser-winner  | BE-AR |  1173.91 | 1033.60, 1314.22 | < .001
loser-loser   | AE-BR |    99.84 |   82.39,  117.29 | < .001
loser-loser   | AE-AR |   157.77 |  130.45,  185.08 | < .001
loser-winner  | AE-BE |   281.86 |  247.46,  316.25 | < .001
loser-winner  | AE-AE |    46.91 |  -45.85,  139.67 | 0.322 
loser-winner  | AE-BR |  -527.09 | -647.23, -406.96 | < .001
loser-winner  | AE-AR |  1380.94 | 1270.35, 1491.52 | < .001
loser-loser   | BR-AR |    57.93 |   41.81,   74.05 | < .001
loser-winner  | BR-BE |   182.02 |  154.70,  209.34 | < .001
loser-winner  | BR-AE |   -52.93 | -138.79,   32.93 | 0.235 
loser-winner  | BR-BR |  -626.93 | -733.02, -520.84 | < .001
loser-winner  | BR-AR |  1281.10 | 1156.54, 1405.65 | < .001
loser-winner  | AR-BE |   124.09 |   95.06,  153.12 | < .001
loser-winner  | AR-AE |  -110.86 | -194.56,  -27.15 | 0.010 
loser-winner  | AR-BR |  -684.86 | -783.65, -586.06 | < .001
loser-winner  | AR-AR |  1223.17 | 1089.89, 1356.46 | < .001
winner-winner | BE-AE |  -234.95 | -322.20, -147.70 | < .001
winner-winner | BE-BR |  -808.95 | -911.92, -705.97 | < .001
winner-winner | BE-AR |  1099.08 |  965.61, 1232.55 | < .001
winner-winner | AE-BR |  -574.00 | -681.31, -466.69 | < .001
winner-winner | AE-AR |  1334.03 | 1156.97, 1511.08 | < .001
winner-winner | BR-AR |  1908.03 | 1679.82, 2136.24 | < .001

Plot: Basic

Effects: Phase x Outcome

Compute

xFit06xPhRetweets: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)

===================================================================== 

# Average predicted counts of LikeCount

Outcome: loser

Phase | Predicted |           95% CI
------------------------------------
BE    |    293.00 |  244.73,  341.26
AE    |    675.67 |  561.96,  789.37
BR    |    471.96 |  392.83,  551.09
AR    |    551.20 |  459.36,  643.03

Outcome: winner

Phase | Predicted |           95% CI
------------------------------------
BE    |    947.18 |  855.53, 1038.83
AE    |   2090.05 | 1890.03, 2290.06
BR    |   3330.59 | 3016.62, 3644.56
AR    |   1623.61 | 1462.93, 1784.29

===================================================================== 

Phase | Outcome | Predicted |           95% CI |      p
-------------------------------------------------------
BE    |   loser |    293.00 |  244.73,  341.26 | < .001
AE    |   loser |    675.67 |  561.96,  789.37 | < .001
BR    |   loser |    471.96 |  392.83,  551.09 | < .001
AR    |   loser |    551.20 |  459.36,  643.03 | < .001
BE    |  winner |    947.18 |  855.53, 1038.83 | < .001
AE    |  winner |   2090.05 | 1890.03, 2290.06 | < .001
BR    |  winner |   3330.59 | 3016.62, 3644.56 | < .001
AR    |  winner |   1623.61 | 1462.93, 1784.29 | < .001

===================================================================== 

# Pairwise comparisons

Phase |       Outcome | Contrast |             95% CI |      p
--------------------------------------------------------------
BE-AE |   loser-loser |  -382.67 |  -448.34,  -317.00 | < .001
BE-BR |   loser-loser |  -178.96 |  -210.09,  -147.84 | < .001
BE-AR |   loser-loser |  -258.20 |  -302.04,  -214.36 | < .001
BE-BE |  loser-winner |  -654.18 |  -794.06,  -514.31 | < .001
BE-AE |  loser-winner | -1797.05 | -2045.29, -1548.81 | < .001
BE-BR |  loser-winner | -3037.60 | -3399.79, -2675.40 | < .001
BE-AR |  loser-winner | -1330.62 | -1539.52, -1121.71 | < .001
AE-BR |   loser-loser |   203.71 |   168.33,   239.08 | < .001
AE-AR |   loser-loser |   124.47 |   100.92,   148.01 | < .001
AE-BE |  loser-winner |  -271.51 |  -476.75,   -66.27 | 0.010 
AE-AE |  loser-winner | -1414.38 | -1727.95, -1100.81 | < .001
AE-BR |  loser-winner | -2654.93 | -3082.44, -2227.41 | < .001
AE-AR |  loser-winner |  -947.95 | -1222.20,  -673.69 | < .001
BR-AR |   loser-loser |   -79.24 |   -93.57,   -64.90 | < .001
BR-BE |  loser-winner |  -475.22 |  -645.92,  -304.52 | < .001
BR-AE |  loser-winner | -1618.09 | -1897.15, -1339.03 | < .001
BR-BR |  loser-winner | -2858.63 | -3251.65, -2465.62 | < .001
BR-AR |  loser-winner | -1151.65 | -1391.39,  -911.92 | < .001
AR-BE |  loser-winner |  -395.98 |  -579.36,  -212.61 | < .001
AR-AE |  loser-winner | -1538.85 | -1830.57, -1247.13 | < .001
AR-BR |  loser-winner | -2779.40 | -3185.06, -2373.73 | < .001
AR-AR |  loser-winner | -1072.42 | -1324.82,  -820.02 | < .001
BE-AE | winner-winner | -1142.87 | -1251.37, -1034.37 | < .001
BE-BR | winner-winner | -2383.41 | -2605.82, -2161.01 | < .001
BE-AR | winner-winner |  -676.43 |  -745.61,  -607.26 | < .001
AE-BR | winner-winner | -1240.55 | -1354.71, -1126.38 | < .001
AE-AR | winner-winner |   466.43 |   426.78,   506.09 | < .001
BR-AR | winner-winner |  1706.98 |  1553.60,  1860.36 | < .001

Plot: Basic

Effects: Agency x Phase

Compute

xFit06xPhRetweets: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)

===================================================================== 

# Average predicted counts of LikeCount

Phase: BE

Agency | Predicted |          95% CI
------------------------------------
    -3 |    940.79 | 813.19, 1068.40
    -2 |    899.62 | 838.94,  960.29
    -1 |    835.33 | 814.31,  856.36
     0 |    749.99 | 745.70,  754.28
     1 |    660.34 | 657.71,  662.96
     2 |    576.82 | 573.02,  580.61
     3 |    502.55 | 498.62,  506.47

Phase: AE

Agency | Predicted |           95% CI
-------------------------------------
    -3 |    734.40 |  309.89, 1158.92
    -2 |   1062.47 |  879.60, 1245.34
    -1 |   1294.72 | 1248.78, 1340.65
     0 |   1480.29 | 1473.50, 1487.07
     1 |   1672.68 | 1667.18, 1678.17
     2 |   1906.79 | 1896.31, 1917.26
     3 |   2212.30 | 2196.46, 2228.15

Phase: BR

Agency | Predicted |           95% CI
-------------------------------------
    -3 |    694.61 |  566.90,  822.31
    -2 |   1003.39 |  943.44, 1063.33
    -1 |   1406.87 | 1384.31, 1429.42
     0 |   1944.84 | 1939.27, 1950.41
     1 |   2670.63 | 2665.84, 2675.42
     2 |   3655.56 | 3647.34, 3663.79
     3 |   4995.85 | 4983.38, 5008.33

Phase: AR

Agency | Predicted |           95% CI
-------------------------------------
    -3 |   6293.90 | 6221.99, 6365.80
    -2 |   3804.98 | 3767.93, 3842.03
    -1 |   2339.06 | 2323.11, 2355.01
     0 |   1480.00 | 1475.61, 1484.39
     1 |    981.28 |  977.40,  985.17
     2 |    696.97 |  690.73,  703.22
     3 |    540.76 |  533.67,  547.84

===================================================================== 

# (Average) Linear trend for Agency

Phase |  Slope |         95% CI |      p
----------------------------------------
BE    |   0.34 | -12.53,  13.21 | 0.959 
AE    | 207.36 | 176.49, 238.24 | < .001
BR    | 107.53 |  91.27, 123.78 | < .001
AR    |  49.60 |  34.97,  64.23 | < .001

===================================================================== 

# (Average) Linear trend for Agency

Phase | Contrast |           95% CI |      p
--------------------------------------------
BE-AE |  -207.03 | -240.43, -173.62 | < .001
BE-BR |  -107.19 | -127.89,  -86.48 | < .001
BE-AR |   -49.26 |  -68.73,  -29.79 | < .001
AE-BR |    99.84 |   82.39,  117.29 | < .001
AE-AR |   157.77 |  130.45,  185.08 | < .001
BR-AR |    57.93 |   41.81,   74.05 | < .001

Plot: Basic

Effects: Phase

Compute

xFit06xPhRetweets: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)

===================================================================== 

# Average predicted counts of LikeCount

Phase | Predicted |           95% CI
------------------------------------
BE    |    705.67 |  703.64,  707.71
AE    |   1567.55 | 1563.90, 1571.19
BR    |   2300.50 | 2297.19, 2303.81
AR    |   1210.33 | 1207.77, 1212.89

===================================================================== 

Phase | Predicted |           95% CI |      p
---------------------------------------------
BE    |    705.67 |  703.64,  707.71 | < .001
AE    |   1567.55 | 1563.90, 1571.19 | < .001
BR    |   2300.50 | 2297.19, 2303.81 | < .001
AR    |   1210.33 | 1207.77, 1212.89 | < .001

===================================================================== 

# Pairwise comparisons

Phase | Contrast |             95% CI |      p
----------------------------------------------
BE-AE |  -861.87 |  -866.06,  -857.69 | < .001
BE-BR | -1594.83 | -1598.73, -1590.92 | < .001
BE-AR |  -504.66 |  -507.94,  -501.38 | < .001
AE-BR |  -732.95 |  -737.91,  -728.00 | < .001
AE-AR |   357.21 |   352.74,   361.69 | < .001
BR-AR |  1090.17 |  1085.95,  1094.38 | < .001

Plot: Basic

Effects: Agency

Compute

xFit06xPhRetweets: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)

===================================================================== 

# Average predicted counts of LikeCount

Agency | Predicted |           95% CI
-------------------------------------
    -3 |   2097.24 | 1958.79, 2235.70
    -2 |   1679.69 | 1618.88, 1740.49
    -1 |   1495.51 | 1479.04, 1511.97
     0 |   1469.94 | 1467.14, 1472.73
     1 |   1579.21 | 1577.17, 1581.25
     2 |   1820.50 | 1817.07, 1823.92
     3 |   2207.40 | 2202.46, 2212.34

===================================================================== 

# (Average) Linear trend for Agency

Slope  |         95% CI |      p
--------------------------------
110.86 | 106.83, 114.90 | < .001

===================================================================== 

# (Average) Linear trend for Agency

Slope  |         95% CI |      p
--------------------------------
110.86 | 106.83, 114.90 | < .001

Plot: Basic

Tabulate glmmTMB Models

	Like Count		Retweet Count
Predictors	Incidence Rate Ratios	CI	Incidence Rate Ratios	CI
(Intercept)	54.85 ***	47.88 – 62.83	21.17 ***	18.73 – 23.94
Agency	0.84 ***	0.84 – 0.85	0.75 ***	0.74 – 0.75
Phase [AE]	1.90 ***	1.90 – 1.90	1.09 ***	1.09 – 1.09
Phase [BR]	2.42 ***	2.41 – 2.42	1.52 ***	1.51 – 1.52
Phase [AR]	1.89 ***	1.88 – 1.89	1.32 ***	1.32 – 1.33
Agency × Phase [AE]	1.27 ***	1.27 – 1.27	1.47 ***	1.46 – 1.47
Agency × Phase [BR]	1.67 ***	1.67 – 1.68	1.72 ***	1.72 – 1.73
Agency × Phase [AR]	0.74 ***	0.74 – 0.74	0.78 ***	0.78 – 0.78
Zero-Inflated Model
(Intercept)	0.06 ***	0.05 – 0.07	0.08 ***	0.07 – 0.09
Agency	0.38 ***	0.30 – 0.47	0.52 ***	0.43 – 0.63
Phase [AE]	0.89	0.75 – 1.06	1.25 **	1.08 – 1.44
Phase [BR]	0.66 ***	0.55 – 0.79	1.10	0.95 – 1.26
Phase [AR]	0.52 ***	0.43 – 0.64	0.92	0.79 – 1.07
Agency × Phase [AE]	0.89	0.64 – 1.24	0.64 **	0.49 – 0.84
Agency × Phase [BR]	1.00	0.72 – 1.40	0.73 *	0.56 – 0.93
Agency × Phase [AR]	0.97	0.66 – 1.41	0.59 ***	0.44 – 0.78
Random Effects
σ2	0.00		0.00
τ00	4.01 Name		3.22 Name
ICC	1.00		1.00
N	847 Name		847 Name
Observations	60000		60000
Marginal R2 / Conditional R2	0.044 / 1.000		0.024 / 1.000
* p<0.05   ** p<0.01   *** p<0.001

./data/20240428T200156-politicians-aux-analysis/n0001-init//n0001-models-phase-i0008-all/x-summary-tab-model-i0001-base.html 

• tab_model

Tabulate ALL glmmTMB Models

	Like Count		Retweet Count		Like Count		Like Count
Predictors	Incidence Rate Ratios	CI	Incidence Rate Ratios	CI	Incidence Rate Ratios	CI	Incidence Rate Ratios	CI
(Intercept)	54.85 ***	47.88 – 62.83	21.17 ***	18.73 – 23.94	30.07 ***	24.65 – 36.69	30.07 ***	24.65 – 36.69
Agency	0.84 ***	0.84 – 0.85	0.75 ***	0.74 – 0.75	0.79 ***	0.79 – 0.79	0.79 ***	0.79 – 0.79
Phase [AE]	1.90 ***	1.90 – 1.90	1.09 ***	1.09 – 1.09	1.75 ***	1.74 – 1.75	1.75 ***	1.74 – 1.75
Phase [BR]	2.42 ***	2.41 – 2.42	1.52 ***	1.51 – 1.52	1.25 ***	1.25 – 1.25	1.25 ***	1.25 – 1.25
Phase [AR]	1.89 ***	1.88 – 1.89	1.32 ***	1.32 – 1.33	1.61 ***	1.61 – 1.62	1.61 ***	1.61 – 1.62
Agency × Phase [AE]	1.27 ***	1.27 – 1.27	1.47 ***	1.46 – 1.47	1.86 ***	1.85 – 1.87	1.86 ***	1.85 – 1.87
Agency × Phase [BR]	1.67 ***	1.67 – 1.68	1.72 ***	1.72 – 1.73	1.71 ***	1.71 – 1.72	1.71 ***	1.71 – 1.72
Agency × Phase [AR]	0.74 ***	0.74 – 0.74	0.78 ***	0.78 – 0.78	1.40 ***	1.39 – 1.41	1.40 ***	1.39 – 1.41
Outcome [winner]					2.95 ***	2.27 – 3.83	2.95 ***	2.27 – 3.83
Agency × Outcome [winner]					1.12 ***	1.11 – 1.12	1.12 ***	1.11 – 1.12
Phase [AE] × Outcome [winner]					1.15 ***	1.15 – 1.15	1.15 ***	1.15 – 1.15
Phase [BR] × Outcome [winner]					2.24 ***	2.23 – 2.24	2.24 ***	2.23 – 2.24
Phase [AR] × Outcome [winner]					1.24 ***	1.24 – 1.24	1.24 ***	1.24 – 1.24
(Agency × Phase [AE]) × Outcome [winner]					0.65 ***	0.64 – 0.65	0.65 ***	0.64 – 0.65
(Agency × Phase [BR]) × Outcome [winner]					0.90 ***	0.90 – 0.91	0.90 ***	0.90 – 0.91
(Agency × Phase [AR]) × Outcome [winner]					0.48 ***	0.48 – 0.49	0.48 ***	0.48 – 0.49
Zero-Inflated Model
(Intercept)	0.06 ***	0.05 – 0.07	0.08 ***	0.07 – 0.09	0.10 ***	0.09 – 0.11	0.10 ***	0.09 – 0.11
Agency	0.38 ***	0.30 – 0.47	0.52 ***	0.43 – 0.63	0.34 ***	0.26 – 0.45	0.34 ***	0.26 – 0.45
Phase [AE]	0.89	0.75 – 1.06	1.25 **	1.08 – 1.44	1.22	0.99 – 1.50	1.22	0.99 – 1.50
Phase [BR]	0.66 ***	0.55 – 0.79	1.10	0.95 – 1.26	0.91	0.74 – 1.12	0.91	0.74 – 1.12
Phase [AR]	0.52 ***	0.43 – 0.64	0.92	0.79 – 1.07	0.88	0.71 – 1.11	0.88	0.71 – 1.11
Agency × Phase [AE]	0.89	0.64 – 1.24	0.64 **	0.49 – 0.84	1.82 **	1.22 – 2.70	1.82 **	1.22 – 2.70
Agency × Phase [BR]	1.00	0.72 – 1.40	0.73 *	0.56 – 0.93	1.90 **	1.28 – 2.80	1.90 **	1.28 – 2.80
Agency × Phase [AR]	0.97	0.66 – 1.41	0.59 ***	0.44 – 0.78	1.78 *	1.14 – 2.80	1.78 *	1.14 – 2.80
Outcome [winner]					0.26 ***	0.19 – 0.34	0.26 ***	0.19 – 0.34
Agency × Outcome [winner]					1.86 *	1.12 – 3.11	1.86 *	1.12 – 3.11
Phase [AE] × Outcome [winner]					0.62 *	0.41 – 0.93	0.62 *	0.41 – 0.93
Phase [BR] × Outcome [winner]					0.36 ***	0.22 – 0.58	0.36 ***	0.22 – 0.58
Phase [AR] × Outcome [winner]					0.29 ***	0.17 – 0.50	0.29 ***	0.17 – 0.50
(Agency × Phase [AE]) × Outcome [winner]					0.27 ***	0.13 – 0.58	0.27 ***	0.13 – 0.58
(Agency × Phase [BR]) × Outcome [winner]					0.36 *	0.15 – 0.84	0.36 *	0.15 – 0.84
(Agency × Phase [AR]) × Outcome [winner]					1.03	0.43 – 2.48	1.03	0.43 – 2.48
Random Effects
σ2	0.00		0.00		0.00		0.00
τ00	4.01 Name		3.22 Name		3.63 Name		3.63 Name
ICC	1.00		1.00		1.00		1.00
N	847 Name		847 Name		847 Name		847 Name
Observations	60000		60000		60000		60000
Marginal R2 / Conditional R2	0.044 / 1.000		0.024 / 1.000		0.135 / 1.000		0.135 / 1.000
* p<0.05   ** p<0.01   *** p<0.001

./data/20240428T200156-politicians-aux-analysis/n0001-init//n0001-models-phase-i0008-all/x-summary-tab-model-i0002-ALL.html 

• tab_model

Report xFit05aPhLikes

We fitted a zero-inflated poisson mixed model (estimated using ML and nlminb
optimizer) to predict LikeCount with Agency and Phase (formula: LikeCount ~
Agency * Phase). The model included Name as random effect (formula: ~1 | Name).
The model's total explanatory power is substantial (conditional R2 = 1.00) and
the part related to the fixed effects alone (marginal R2) is of 0.04. The
model's intercept, corresponding to Agency = 0 and Phase = BE, is at 4.00 (95%
CI [3.87, 4.14], p < .001). Within this model:

  - The effect of Agency is statistically significant and negative (beta = -0.17,
95% CI [-0.17, -0.17], p < .001; Std. beta = -0.06, 95% CI [-0.06, -0.06])
  - The effect of Phase [AE] is statistically significant and positive (beta =
0.64, 95% CI [0.64, 0.64], p < .001; Std. beta = 0.76, 95% CI [0.76, 0.76])
  - The effect of Phase [BR] is statistically significant and positive (beta =
0.88, 95% CI [0.88, 0.88], p < .001; Std. beta = 1.14, 95% CI [1.13, 1.14])
  - The effect of Phase [AR] is statistically significant and positive (beta =
0.63, 95% CI [0.63, 0.64], p < .001; Std. beta = 0.49, 95% CI [0.49, 0.49])
  - The effect of Agency × Phase [AE] is statistically significant and positive
(beta = 0.24, 95% CI [0.24, 0.24], p < .001; Std. beta = 0.09, 95% CI [0.09,
0.09])
  - The effect of Agency × Phase [BR] is statistically significant and positive
(beta = 0.51, 95% CI [0.51, 0.52], p < .001; Std. beta = 0.19, 95% CI [0.19,
0.19])
  - The effect of Agency × Phase [AR] is statistically significant and negative
(beta = -0.30, 95% CI [-0.30, -0.30], p < .001; Std. beta = -0.11, 95% CI
[-0.11, -0.11])
  - The effect of Agency is statistically significant and negative (beta = -0.98,
95% CI [-1.21, -0.75], p < .001; Std. beta = -0.36, 95% CI [-0.45, -0.27])
  - The effect of Phase [AE] is statistically non-significant and negative (beta
= -0.11, 95% CI [-0.29, 0.06], p = 0.205; Std. beta = -0.17, 95% CI [-0.30,
-0.04])
  - The effect of Phase [BR] is statistically significant and negative (beta =
-0.41, 95% CI [-0.59, -0.23], p < .001; Std. beta = -0.41, 95% CI [-0.55,
-0.27])
  - The effect of Phase [AR] is statistically significant and negative (beta =
-0.65, 95% CI [-0.85, -0.44], p < .001; Std. beta = -0.66, 95% CI [-0.81,
-0.51])
  - The effect of Agency × Phase [AE] is statistically non-significant and
negative (beta = -0.12, 95% CI [-0.45, 0.22], p = 0.492; Std. beta = -0.04, 95%
CI [-0.17, 0.08])
  - The effect of Agency × Phase [BR] is statistically non-significant and
positive (beta = 3.81e-03, 95% CI [-0.33, 0.33], p = 0.982; Std. beta =
9.86e-04, 95% CI [-0.12, 0.12])
  - The effect of Agency × Phase [AR] is statistically non-significant and
negative (beta = -0.03, 95% CI [-0.41, 0.35], p = 0.871; Std. beta = -0.01, 95%
CI [-0.15, 0.13])

Standardized parameters were obtained by fitting the model on a standardized
version of the dataset. 95% Confidence Intervals (CIs) and p-values were
computed using a Wald z-distribution approximation.

Report xFit06aPhRetweets

We fitted a zero-inflated poisson mixed model (estimated using ML and nlminb
optimizer) to predict RetweetCount with Agency and Phase (formula: RetweetCount
~ Agency * Phase). The model included Name as random effect (formula: ~1 |
Name). The model's total explanatory power is substantial (conditional R2 =
1.00) and the part related to the fixed effects alone (marginal R2) is of 0.02.
The model's intercept, corresponding to Agency = 0 and Phase = BE, is at 3.05
(95% CI [2.93, 3.18], p < .001). Within this model:

  - The effect of Agency is statistically significant and negative (beta = -0.29,
95% CI [-0.29, -0.29], p < .001; Std. beta = -0.11, 95% CI [-0.11, -0.11])
  - The effect of Phase [AE] is statistically significant and positive (beta =
0.09, 95% CI [0.08, 0.09], p < .001; Std. beta = 0.27, 95% CI [0.27, 0.28])
  - The effect of Phase [BR] is statistically significant and positive (beta =
0.42, 95% CI [0.41, 0.42], p < .001; Std. beta = 0.68, 95% CI [0.68, 0.69])
  - The effect of Phase [AR] is statistically significant and positive (beta =
0.28, 95% CI [0.28, 0.28], p < .001; Std. beta = 0.16, 95% CI [0.16, 0.16])
  - The effect of Agency × Phase [AE] is statistically significant and positive
(beta = 0.38, 95% CI [0.38, 0.39], p < .001; Std. beta = 0.14, 95% CI [0.14,
0.14])
  - The effect of Agency × Phase [BR] is statistically significant and positive
(beta = 0.54, 95% CI [0.54, 0.55], p < .001; Std. beta = 0.20, 95% CI [0.20,
0.20])
  - The effect of Agency × Phase [AR] is statistically significant and negative
(beta = -0.25, 95% CI [-0.25, -0.24], p < .001; Std. beta = -0.09, 95% CI
[-0.09, -0.09])
  - The effect of Agency is statistically significant and negative (beta = -0.65,
95% CI [-0.84, -0.46], p < .001; Std. beta = -0.24, 95% CI [-0.31, -0.17])
  - The effect of Phase [AE] is statistically significant and positive (beta =
0.22, 95% CI [0.08, 0.37], p = 0.002; Std. beta = 7.69e-03, 95% CI [-0.09,
0.11])
  - The effect of Phase [BR] is statistically non-significant and positive (beta
= 0.09, 95% CI [-0.05, 0.23], p = 0.191; Std. beta = -0.06, 95% CI [-0.17,
0.04])
  - The effect of Phase [AR] is statistically non-significant and negative (beta
= -0.08, 95% CI [-0.23, 0.07], p = 0.290; Std. beta = -0.34, 95% CI [-0.45,
-0.23])
  - The effect of Agency × Phase [AE] is statistically significant and negative
(beta = -0.44, 95% CI [-0.71, -0.18], p = 0.001; Std. beta = -0.16, 95% CI
[-0.26, -0.07])
  - The effect of Agency × Phase [BR] is statistically significant and negative
(beta = -0.32, 95% CI [-0.57, -0.07], p = 0.013; Std. beta = -0.12, 95% CI
[-0.21, -0.02])
  - The effect of Agency × Phase [AR] is statistically significant and negative
(beta = -0.53, 95% CI [-0.81, -0.25], p < .001; Std. beta = -0.20, 95% CI
[-0.30, -0.09])

Standardized parameters were obtained by fitting the model on a standardized
version of the dataset. 95% Confidence Intervals (CIs) and p-values were
computed using a Wald z-distribution approximation.

Report xFit05xPhLikes

We fitted a zero-inflated poisson mixed model (estimated using ML and nlminb
optimizer) to predict LikeCount with Agency, Phase and Outcome (formula:
LikeCount ~ Agency * Phase * Outcome). The model included Name as random effect
(formula: ~1 | Name). The model's total explanatory power is substantial
(conditional R2 = 1.00) and the part related to the fixed effects alone
(marginal R2) is of 0.14. The model's intercept, corresponding to Agency = 0,
Phase = BE and Outcome = loser, is at 3.40 (95% CI [3.20, 3.60], p < .001).
Within this model:

  - The effect of Agency is statistically significant and negative (beta = -0.24,
95% CI [-0.24, -0.23], p < .001; Std. beta = -0.09, 95% CI [-0.09, -0.09])
  - The effect of Phase [AE] is statistically significant and positive (beta =
0.56, 95% CI [0.56, 0.56], p < .001; Std. beta = 0.86, 95% CI [0.86, 0.86])
  - The effect of Phase [BR] is statistically significant and positive (beta =
0.22, 95% CI [0.22, 0.22], p < .001; Std. beta = 0.49, 95% CI [0.48, 0.49])
  - The effect of Phase [AR] is statistically significant and positive (beta =
0.48, 95% CI [0.48, 0.48], p < .001; Std. beta = 0.64, 95% CI [0.64, 0.64])
  - The effect of Outcome [winner] is statistically significant and positive
(beta = 1.08, 95% CI [0.82, 1.34], p < .001; Std. beta = 1.09, 95% CI [0.83,
1.36])
  - The effect of Agency × Phase [AE] is statistically significant and positive
(beta = 0.62, 95% CI [0.61, 0.62], p < .001; Std. beta = 0.23, 95% CI [0.23,
0.23])
  - The effect of Agency × Phase [BR] is statistically significant and positive
(beta = 0.54, 95% CI [0.53, 0.54], p < .001; Std. beta = 0.20, 95% CI [0.20,
0.20])
  - The effect of Agency × Phase [AR] is statistically significant and positive
(beta = 0.34, 95% CI [0.33, 0.34], p < .001; Std. beta = 0.12, 95% CI [0.12,
0.13])
  - The effect of Agency × Outcome [winner] is statistically significant and
positive (beta = 0.11, 95% CI [0.10, 0.11], p < .001; Std. beta = 0.04, 95% CI
[0.04, 0.04])
  - The effect of Phase [AE] × Outcome [winner] is statistically significant and
positive (beta = 0.14, 95% CI [0.14, 0.14], p < .001; Std. beta = -0.08, 95% CI
[-0.08, -0.07])
  - The effect of Phase [BR] × Outcome [winner] is statistically significant and
positive (beta = 0.80, 95% CI [0.80, 0.81], p < .001; Std. beta = 0.76, 95% CI
[0.75, 0.76])
  - The effect of Phase [AR] × Outcome [winner] is statistically significant and
positive (beta = 0.21, 95% CI [0.21, 0.22], p < .001; Std. beta = -0.14, 95% CI
[-0.15, -0.14])
  - The effect of (Agency × Phase [AE]) × Outcome [winner] is statistically
significant and negative (beta = -0.44, 95% CI [-0.44, -0.43], p < .001; Std.
beta = -0.16, 95% CI [-0.16, -0.16])
  - The effect of (Agency × Phase [BR]) × Outcome [winner] is statistically
significant and negative (beta = -0.10, 95% CI [-0.11, -0.10], p < .001; Std.
beta = -0.04, 95% CI [-0.04, -0.04])
  - The effect of (Agency × Phase [AR]) × Outcome [winner] is statistically
significant and negative (beta = -0.73, 95% CI [-0.73, -0.72], p < .001; Std.
beta = -0.27, 95% CI [-0.27, -0.27])
  - The effect of Agency is statistically significant and negative (beta = -1.08,
95% CI [-1.36, -0.80], p < .001; Std. beta = -0.38, 95% CI [-0.48, -0.28])
  - The effect of Phase [AE] is statistically non-significant and positive (beta
= 0.20, 95% CI [-9.68e-03, 0.40], p = 0.062; Std. beta = 0.46, 95% CI [0.29,
0.62])
  - The effect of Phase [BR] is statistically non-significant and negative (beta
= -0.09, 95% CI [-0.30, 0.11], p = 0.369; Std. beta = 0.22, 95% CI [0.05,
0.38])
  - The effect of Phase [AR] is statistically non-significant and negative (beta
= -0.12, 95% CI [-0.35, 0.10], p = 0.290; Std. beta = 0.15, 95% CI [-0.04,
0.35])
  - The effect of Outcome [winner] is statistically significant and negative
(beta = -1.37, 95% CI [-1.66, -1.08], p < .001; Std. beta = -1.07, 95% CI
[-1.25, -0.88])
  - The effect of Agency × Phase [AE] is statistically significant and positive
(beta = 0.60, 95% CI [0.20, 0.99], p = 0.003; Std. beta = 0.21, 95% CI [0.06,
0.35])
  - The effect of Agency × Phase [BR] is statistically significant and positive
(beta = 0.64, 95% CI [0.25, 1.03], p = 0.001; Std. beta = 0.24, 95% CI [0.10,
0.39])
  - The effect of Agency × Phase [AR] is statistically significant and positive
(beta = 0.58, 95% CI [0.13, 1.03], p = 0.012; Std. beta = 0.21, 95% CI [0.04,
0.37])
  - The effect of Agency × Outcome [winner] is statistically significant and
positive (beta = 0.62, 95% CI [0.11, 1.13], p = 0.017; Std. beta = 0.24, 95% CI
[0.06, 0.43])
  - The effect of Phase [AE] × Outcome [winner] is statistically significant and
negative (beta = -0.48, 95% CI [-0.89, -0.07], p = 0.021; Std. beta = -1.04,
95% CI [-1.33, -0.76])
  - The effect of Phase [BR] × Outcome [winner] is statistically significant and
negative (beta = -1.03, 95% CI [-1.51, -0.55], p < .001; Std. beta = -1.41, 95%
CI [-1.74, -1.08])
  - The effect of Phase [AR] × Outcome [winner] is statistically significant and
negative (beta = -1.22, 95% CI [-1.75, -0.70], p < .001; Std. beta = -1.14, 95%
CI [-1.46, -0.82])
  - The effect of (Agency × Phase [AE]) × Outcome [winner] is statistically
significant and negative (beta = -1.30, 95% CI [-2.06, -0.55], p < .001; Std.
beta = -0.43, 95% CI [-0.71, -0.16])
  - The effect of (Agency × Phase [BR]) × Outcome [winner] is statistically
significant and negative (beta = -1.03, 95% CI [-1.87, -0.18], p = 0.018; Std.
beta = -0.35, 95% CI [-0.65, -0.05])
  - The effect of (Agency × Phase [AR]) × Outcome [winner] is statistically
non-significant and positive (beta = 0.03, 95% CI [-0.84, 0.91], p = 0.941;
Std. beta = -0.02, 95% CI [-0.34, 0.29])

Standardized parameters were obtained by fitting the model on a standardized
version of the dataset. 95% Confidence Intervals (CIs) and p-values were
computed using a Wald z-distribution approximation.

Report xFit06xPhRetweets

We fitted a zero-inflated poisson mixed model (estimated using ML and nlminb
optimizer) to predict LikeCount with Agency, Phase and Outcome (formula:
LikeCount ~ Agency * Phase * Outcome). The model included Name as random effect
(formula: ~1 | Name). The model's total explanatory power is substantial
(conditional R2 = 1.00) and the part related to the fixed effects alone
(marginal R2) is of 0.14. The model's intercept, corresponding to Agency = 0,
Phase = BE and Outcome = loser, is at 3.40 (95% CI [3.20, 3.60], p < .001).
Within this model:

  - The effect of Agency is statistically significant and negative (beta = -0.24,
95% CI [-0.24, -0.23], p < .001; Std. beta = -0.09, 95% CI [-0.09, -0.09])
  - The effect of Phase [AE] is statistically significant and positive (beta =
0.56, 95% CI [0.56, 0.56], p < .001; Std. beta = 0.86, 95% CI [0.86, 0.86])
  - The effect of Phase [BR] is statistically significant and positive (beta =
0.22, 95% CI [0.22, 0.22], p < .001; Std. beta = 0.49, 95% CI [0.48, 0.49])
  - The effect of Phase [AR] is statistically significant and positive (beta =
0.48, 95% CI [0.48, 0.48], p < .001; Std. beta = 0.64, 95% CI [0.64, 0.64])
  - The effect of Outcome [winner] is statistically significant and positive
(beta = 1.08, 95% CI [0.82, 1.34], p < .001; Std. beta = 1.09, 95% CI [0.83,
1.36])
  - The effect of Agency × Phase [AE] is statistically significant and positive
(beta = 0.62, 95% CI [0.61, 0.62], p < .001; Std. beta = 0.23, 95% CI [0.23,
0.23])
  - The effect of Agency × Phase [BR] is statistically significant and positive
(beta = 0.54, 95% CI [0.53, 0.54], p < .001; Std. beta = 0.20, 95% CI [0.20,
0.20])
  - The effect of Agency × Phase [AR] is statistically significant and positive
(beta = 0.34, 95% CI [0.33, 0.34], p < .001; Std. beta = 0.12, 95% CI [0.12,
0.13])
  - The effect of Agency × Outcome [winner] is statistically significant and
positive (beta = 0.11, 95% CI [0.10, 0.11], p < .001; Std. beta = 0.04, 95% CI
[0.04, 0.04])
  - The effect of Phase [AE] × Outcome [winner] is statistically significant and
positive (beta = 0.14, 95% CI [0.14, 0.14], p < .001; Std. beta = -0.08, 95% CI
[-0.08, -0.07])
  - The effect of Phase [BR] × Outcome [winner] is statistically significant and
positive (beta = 0.80, 95% CI [0.80, 0.81], p < .001; Std. beta = 0.76, 95% CI
[0.75, 0.76])
  - The effect of Phase [AR] × Outcome [winner] is statistically significant and
positive (beta = 0.21, 95% CI [0.21, 0.22], p < .001; Std. beta = -0.14, 95% CI
[-0.15, -0.14])
  - The effect of (Agency × Phase [AE]) × Outcome [winner] is statistically
significant and negative (beta = -0.44, 95% CI [-0.44, -0.43], p < .001; Std.
beta = -0.16, 95% CI [-0.16, -0.16])
  - The effect of (Agency × Phase [BR]) × Outcome [winner] is statistically
significant and negative (beta = -0.10, 95% CI [-0.11, -0.10], p < .001; Std.
beta = -0.04, 95% CI [-0.04, -0.04])
  - The effect of (Agency × Phase [AR]) × Outcome [winner] is statistically
significant and negative (beta = -0.73, 95% CI [-0.73, -0.72], p < .001; Std.
beta = -0.27, 95% CI [-0.27, -0.27])
  - The effect of Agency is statistically significant and negative (beta = -1.08,
95% CI [-1.36, -0.80], p < .001; Std. beta = -0.38, 95% CI [-0.48, -0.28])
  - The effect of Phase [AE] is statistically non-significant and positive (beta
= 0.20, 95% CI [-9.68e-03, 0.40], p = 0.062; Std. beta = 0.46, 95% CI [0.29,
0.62])
  - The effect of Phase [BR] is statistically non-significant and negative (beta
= -0.09, 95% CI [-0.30, 0.11], p = 0.369; Std. beta = 0.22, 95% CI [0.05,
0.38])
  - The effect of Phase [AR] is statistically non-significant and negative (beta
= -0.12, 95% CI [-0.35, 0.10], p = 0.290; Std. beta = 0.15, 95% CI [-0.04,
0.35])
  - The effect of Outcome [winner] is statistically significant and negative
(beta = -1.37, 95% CI [-1.66, -1.08], p < .001; Std. beta = -1.07, 95% CI
[-1.25, -0.88])
  - The effect of Agency × Phase [AE] is statistically significant and positive
(beta = 0.60, 95% CI [0.20, 0.99], p = 0.003; Std. beta = 0.21, 95% CI [0.06,
0.35])
  - The effect of Agency × Phase [BR] is statistically significant and positive
(beta = 0.64, 95% CI [0.25, 1.03], p = 0.001; Std. beta = 0.24, 95% CI [0.10,
0.39])
  - The effect of Agency × Phase [AR] is statistically significant and positive
(beta = 0.58, 95% CI [0.13, 1.03], p = 0.012; Std. beta = 0.21, 95% CI [0.04,
0.37])
  - The effect of Agency × Outcome [winner] is statistically significant and
positive (beta = 0.62, 95% CI [0.11, 1.13], p = 0.017; Std. beta = 0.24, 95% CI
[0.06, 0.43])
  - The effect of Phase [AE] × Outcome [winner] is statistically significant and
negative (beta = -0.48, 95% CI [-0.89, -0.07], p = 0.021; Std. beta = -1.04,
95% CI [-1.33, -0.76])
  - The effect of Phase [BR] × Outcome [winner] is statistically significant and
negative (beta = -1.03, 95% CI [-1.51, -0.55], p < .001; Std. beta = -1.41, 95%
CI [-1.74, -1.08])
  - The effect of Phase [AR] × Outcome [winner] is statistically significant and
negative (beta = -1.22, 95% CI [-1.75, -0.70], p < .001; Std. beta = -1.14, 95%
CI [-1.46, -0.82])
  - The effect of (Agency × Phase [AE]) × Outcome [winner] is statistically
significant and negative (beta = -1.30, 95% CI [-2.06, -0.55], p < .001; Std.
beta = -0.43, 95% CI [-0.71, -0.16])
  - The effect of (Agency × Phase [BR]) × Outcome [winner] is statistically
significant and negative (beta = -1.03, 95% CI [-1.87, -0.18], p = 0.018; Std.
beta = -0.35, 95% CI [-0.65, -0.05])
  - The effect of (Agency × Phase [AR]) × Outcome [winner] is statistically
non-significant and positive (beta = 0.03, 95% CI [-0.84, 0.91], p = 0.941;
Std. beta = -0.02, 95% CI [-0.34, 0.29])

Standardized parameters were obtained by fitting the model on a standardized
version of the dataset. 95% Confidence Intervals (CIs) and p-values were
computed using a Wald z-distribution approximation.

Save Workspace

Model xFit21aPhOutcome

Fit

xFit21aPhOutcome: [df6] Outcome ~ Agency + (1 | Name)
 Family: binomial  ( logit )
Formula:          Outcome ~ Agency + (1 | Name)
Data: df6

     AIC      BIC   logLik deviance df.resid 
  1346.4   1378.2   -670.2   1340.4   304617 

Random effects:

Conditional model:
 Groups Name        Variance Std.Dev.
 Name   (Intercept) 13586    116.6   
Number of obs: 304620, groups:  Name, 850

Conditional model:
            Estimate Std. Error z value Pr(>|z|)    
(Intercept)  18.8140     0.7048  26.693   <2e-16 ***
Agency        0.1325     0.8099   0.164     0.87    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--------------------------------------------------------------------- 
xFit21aPhOutcome: [df6] Outcome ~ Agency + (1 | Name)
# R2 for Mixed Models

  Conditional R2: 1.000
     Marginal R2: 0.000
--------------------------------------------------------------------- 
xFit21aPhOutcome: [df6] Outcome ~ Agency + (1 | Name)
# Intraclass Correlation Coefficient

    Adjusted ICC: 1.000
  Unadjusted ICC: 1.000
--------------------------------------------------------------------- 
xFit21aPhOutcome: [df6] Outcome ~ Agency + (1 | Name)
# ICC by Group

Group |   ICC
-------------
Name  | 1.000
--------------------------------------------------------------------- 

Save Workspace

List important variables

===================================================================== 

df0 
df2 
df3 
df5 
df6 
df8 

===================================================================== 

fit01aPh 
fit02aPh 
fit03aPh 
fit04aPh 
fit04xPh 
xFit05aPhLikes 
xFit05xPhLikes 
xFit06aPhRetweets 
xFit06xPhRetweets 
xFit21aPhOutcome